Over the past three years, HR leaders have repeatedly been offered similar solutions: implement a chatbot or copilot and expect increased productivity. However, these tools have largely delivered incremental improvements in drafting rather than true transformation.

A significant change is now underway that will fundamentally reshape the HR function.

Agentic AI does not wait for a prompt. It watches for a trigger, decides what needs to happen next, and carries out the work across the tools your team already uses, from the applicant tracking system to payroll to Slack. Instead of a single smart assistant, you get a small workforce of specialized agents handling recruiting, onboarding, compliance, and employee service in parallel. That is the shift this article is about: from AI that helps a person do a task, to AI that runs the task on its own and simply reports back.

The easiest way to see the difference is to compare what each one does when nothing prompts them.

A generative AI assistant sits idle until someone types a question. Ask it to draft an offer letter, and it drafts one. Ask it nothing, and it does nothing.

An agentic system behaves more like a quiet coworker who never clocks out. It notices that a candidate pipeline has stalled for eight days, checks why, and either nudges the recruiter or reschedules interviews on its own. It notices a payroll anomaly before finance does. It notices that engagement scores dropped in one region and flags it to the HR business partner with a summary of what changed.

This is not automation in the old sense, where a system follows a fixed script. Agentic AI reasons through exceptions. It decides which of several possible actions makes sense given the situation, then takes that action, and only loops in a human when the stakes or ambiguity call for it.

This is not a five-year-out concept. It is running in production at companies right now, and the results are concrete enough to plan around.

Recruiting has become an orchestrated pipeline rather than a series of manual steps. An agent can draft a job description from a workforce plan, post it across boards, screen incoming resumes against a skills rubric, rank the shortlist, and negotiate interview times directly with candidates and hiring managers. Recruiters step in for the conversations that actually need a human voice, not the calendar tetris around them. Healthcare organization Wellstar reported that an agentic assistant automated thousands of routine account unlocks and cut internal approval times from several days down to about ninety minutes, freeing staff for higher-value work.

Onboarding has quietly become a coordination problem that agents are well suited to solve. When an offer is accepted, one trigger can set off a chain: provisioning system access, ordering equipment, enrolling the new hire in the right learning paths, and notifying IT, facilities, and the hiring manager, all without someone manually checking five different systems.

Compliance monitoring is moving from a once-a-quarter audit to something closer to continuous coverage. Picture a state changing its family leave rules. An agent tracking regulatory feeds can catch the update within hours, compare it against the company’s current policy, flag the exact clause that needs to change, and hand HR and legal a summary along with a drafted revision, rather than someone discovering the gap during an audit months later.

Employee service is where the volume gains are hardest to ignore. Gartner has tracked HR’s AI adoption climbing from about 19 percent in 2023 to roughly 61 percent by 2025, and a large share of that growth is in service delivery: agents triaging tickets, answering policy questions, updating records, and escalating only the cases that genuinely need a person.

PwC’s analysis of HR sub-processes across the full hire-to-retire lifecycle found that agents can now handle or assist more than half of day-to-day HR work, and closer to 88 percent of purely administrative tasks like forms and routine transactions. Strategy work, culture building, and judgment calls on people decisions remain firmly human territory, and that split is unlikely to move much even as the tools get better.

The phrase sounds abstract until you see it in practice. It simply means multiple agents, each built for a narrow job, working off shared data and shared goals instead of operating as isolated tools.

Think of a recruiting agent, an onboarding agent, and a compliance agent all reading from the same employee record. When a candidate accepts an offer, the recruiting agent’s job ends and it hands context, not just a status update, to the onboarding agent, which already knows the start date, the role, the manager, and the equipment needs. Nobody re-enters that information. Nothing gets lost between systems.

This only works if the underlying data is actually connected. ADP has pointed out that agents can only reason well when they can see across the HRIS, payroll, ATS, and ticketing systems at once. An agent boxed into a single platform behaves like a smart tool. An agent with access across the stack behaves like an orchestrator. The technology is rarely the bottleneck here. Messy, siloed data usually is.

Platforms like Sana, Moveworks, and ServiceNow have built their pitch around exactly this orchestration layer, connecting HR, IT, and finance systems so agents can complete a request end to end instead of stalling out at the edge of one tool.

Microsoft’s research on what it calls “Frontier Firms” describes organizations moving through three stages: people using AI assistants, then human-agent teams working side by side, and eventually human-led operations where agents run day-to-day execution under human direction. That last stage has produced a new kind of job title inside some companies: the “agent boss,” someone whose real work is managing a portfolio of AI agents the way a manager once managed a team of people.

That is not the same as HR disappearing. If anything, the roles that remain get more human, not less. When agents absorb the scheduling, the data entry, and the first-pass screening, HR professionals get their time back for the parts of the job that were always the hardest to automate: coaching a manager through a tough conversation, mediating a conflict, deciding how to handle a genuinely ambiguous case, and shaping the culture that no dashboard can capture.

Josh Bersin’s research on this shift makes a similar point. Companies that redesign the work itself around human-agent partnership, rather than just bolting AI onto existing processes, see the largest gains, sometimes several times the output of teams that never rethought how the work is structured in the first place.

None of this works without guardrails, and the companies getting agentic AI right are the ones treating governance as part of the design, not an afterthought bolted on after something goes wrong.

A few things matter more than the rest:

Clear escalation rules. Scheduling an interview is low stakes. Deciding on a pay adjustment or a termination is not. The best agentic systems are built with explicit boundaries around which decisions an agent can finalize and which ones must land on a person’s desk before anything happens.

Audit trails. Every action an agent takes, and the reasoning behind it, needs to be logged and reviewable. This matters for compliance, and it matters just as much for building trust with employees who want to know a real person is accountable for decisions that affect their work life.

Data quality as a first step, not a side project. An agent is only as good as what it can see. Before scaling agents across the HR stack, the harder and less glamorous work is making sure the HRIS, ATS, payroll, and benefits systems can actually talk to each other.

Regulatory awareness. Laws around pay equity, hiring bias, and algorithmic decision-making are catching up to this technology fast. Explainability is likely to become a requirement rather than a nice-to-have, so building agents that can show their reasoning now will save a lot of retrofitting later.

PwC’s own survey found that while nearly 8 in 10 executives say their companies are already adopting AI agents somewhere in the business, only about 4 in 10 have brought agents into HR specifically. That gap is an opportunity for anyone willing to move now rather than wait for the space to get crowded.

A sensible starting point looks like this:

• Pick one workflow with a clear, measurable pain point, usually recruiting screening or onboarding coordination, and pilot an agent there before attempting anything enterprise-wide.
• Fix the data connections between your core systems before adding more tools on top of a fragmented stack.
• Define escalation and approval rules before the agent goes live, not after the first edge case surfaces.
• Treat the rollout as iterative. Expect to adjust the agent’s rules as you see how it behaves against real cases, rather than expecting it to be right on day one.
• Keep people at the center of anything involving pay, termination, promotion, or other decisions with real consequences for someone’s livelihood.

Agentic AI is not another item on the HR tech shopping list. It is a different operating model, one where routine, cross-system work runs largely on its own and human attention shifts toward judgment, empathy, and the decisions that genuinely need a person behind them.

The organizations that treat this as a chance to redesign how HR work gets done, rather than just automating the same broken process faster, are the ones that will see the biggest gains. The technology is ready sooner than most HR teams expect. The real work now is getting the data, the governance, and the people ready to work alongside it.

What is agentic AI in HR? Agentic AI in HR refers to AI systems that act autonomously across HR workflows. Rather than waiting for a person to ask a question, these agents monitor signals like a stalled hiring pipeline or a compliance change, decide on the right next step, and carry it out across connected systems like the HRIS, ATS, and payroll platform.

How is agentic AI different from a generative AI chatbot? A generative AI chatbot responds when prompted and stops there. An agentic system initiates action on its own, plans a sequence of steps, executes them across multiple tools, and only involves a human when a decision requires judgment or carries real consequences.

Will agentic AI replace HR jobs? Most research points to a shift in focus rather than a wholesale replacement. Agents are taking over administrative and repetitive tasks, while strategic work, culture building, coaching, and sensitive people decisions remain led by humans, often with more time to devote to them than before.

What should HR teams do first before adopting agentic AI? Start by connecting the data across core HR systems, since agents can only reason well with access to a full picture. From there, pilot agents on one well-defined workflow, set clear rules for what requires human approval, and build in audit trails from day one.

Is agentic AI in HR safe from a compliance standpoint? It can be, provided governance is built in from the start. That means explicit escalation rules for sensitive decisions, complete audit logs of agent actions and reasoning, and ongoing attention to evolving regulations around algorithmic decision-making in hiring, pay, and promotion.

AI Assistants Are Old News;Agentic AI Is Transforming HR was originally published in Code Like A Girl on Medium, where people are continuing the conversation by highlighting and responding to this story.

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FREE event at GRR Kitchener, but we kindly as that you reserve your spot online

The post Craft Social appeared first on Grand River Rocks Climbing Gym.

Colonial Acres continues to be one of Waterloo’s most established and desirable neighbourhoods, but not every home is receiving the same response from buyers.

During the 90 days ending July 22, 2026, 21 detached homes had firm sales or completed transactions in Colonial Acres. Sale prices ranged from $705,000 to $2,650,000, reflecting the neighbourhood’s diverse mix of bungalows, side-splits and larger executive properties on mature lots.

Nine homes sold above their final asking price, one sold at asking and 11 sold below asking.

The takeaway for Colonial Acres homeowners is clear: buyers are active, but increasingly selective. The homes achieving the strongest results are generally the ones that offer the right combination of preparation, presentation, pricing and value.

Request a confidential, property-specific home valuation and selling strategy.

As of July 22, 2026:

• Active listings: 5
• Conditionally sold: 1
• Firm sales awaiting closing: 15
• Recently closed sales: 6
• Median sale price: $950,000
• Average sale price: $1,239,036
• Median days on market: 17
• Average days on market: 28
• Sold above asking: 9
• Sold at asking: 1
• Sold below asking: 11

The median price is generally the more useful measure because the average was influenced by several luxury sales above $1.5 million.

Even the median should not be treated as an estimate of every Colonial Acres home. Lot size, street, renovations, layout, condition, square footage, pool, privacy and overall presentation can create substantial differences in value.

The five active detached homes were listed from $875,000 to $2,050,000.

Only one active property was priced below $1 million, while three of the five were listed above $1.5 million. This means the amount and type of competition facing a seller depends greatly on the home’s expected price range.

Several active listings had already accumulated extended market time, experienced a price adjustment or been exposed to the market through a previous listing.

Even in a highly desirable neighbourhood, buyers will resist an asking price that is not supported by the home’s condition, features and current competition.

Looking at all firm and closed sales together does not tell the entire story. Buyer behaviour changed considerably across the different price ranges.

Colonial Acres homes below $1 million

Eleven detached homes sold below $1 million during the 90-day period.

• Median sale price: $859,500
• Median time to sell: 18 days
• Seven sold above asking
• Four sold below asking

This was the most consistently competitive part of the Colonial Acres market. With only one active detached listing below $1 million as of July 22, a well-prepared and accurately priced home in this range may attract strong attention.

That does not mean every property should be intentionally underpriced or held for offers. The right approach depends on the home, current competition and the seller’s priorities.

Colonial Acres homes from $1 million to $1.5 million

Four homes sold within this range.

• Median sale price: $1,255,000
• Median time to sell: 26 days
• None sold above asking
• One sold at asking
• Three sold below asking

Buyers in this segment were more price-sensitive. They closely compared renovation quality, square footage, lot, layout, mechanical updates and overall condition before deciding what they were prepared to pay.

A Colonial Acres address remains valuable, but the neighbourhood alone will not support an asking price that exceeds the complete property’s current market value.

Colonial Acres homes above $1.5 million

Six homes sold for $1.5 million or more.

• Median sale price: $1,820,000
• Two sold above asking
• Four sold below asking
• Selling times ranged from immediate sales to 129 days

This was the most property-specific portion of the market.

Two standout homes attracted immediate competition and sold above asking within two days. Other higher-end properties required considerably more time or sold below their final asking prices.

Luxury buyers will still pay a premium for an exceptional Colonial Acres home, but they have high expectations. They are evaluating design, renovation quality, lot, privacy, outdoor living, architectural features and overall value as a complete package.

More detached homes sold during the most recent 90-day period than during the same period in 2025: 21 compared with 12.

However, the median selling time increased from approximately 10 days to 17 days. The market was busier, but buyers generally took longer to make decisions.

The types of homes sold also differed substantially between the two periods, particularly at the luxury end of the market. For that reason, a simple year-over-year change in the average price would not provide a reliable indication of how an individual Colonial Acres home’s value has changed.

A sold-over-asking headline can be impressive, but it does not always explain how a property actually performed.

A home may sell above its final asking price after being reduced or repositioned. Another may sell slightly below asking while still producing an excellent outcome based on the property’s market value, closing terms and the seller’s goals.

To properly assess a sale, we consider:

• The original and final asking prices
• Previous listings, relaunches and price adjustments
• Total market exposure
• Condition and level of renovation
• Lot size, privacy and street location
• Competing inventory at the time
• Offer conditions, deposit and closing date
• The seller’s overall priorities

A home does not have to be completely renovated to sell well.

In many cases, the best return comes from targeted preparation: completing necessary repairs, refreshing paint, improving lighting, editing furnishings, addressing visible maintenance concerns and professionally staging the property.

The key is knowing which improvements will matter to buyers—and which projects are unlikely to produce a meaningful return.

Based on recent sales and the feedback we are receiving, buyers are responding most favourably to homes offering a strong combination of:

• Mature, private or unusually large lots
• Updated kitchens and bathrooms
• Functional layouts and generous living space
• Finished lower levels
• Flexible space for working from home or extended family
• Pools and well-designed outdoor living areas
• Updated mechanical systems
• Natural light and architectural character
• Professional staging and presentation
• Pricing supported by current market evidence

A home does not have to be completely renovated to sell well.

In many cases, the best return comes from targeted preparation: completing necessary repairs, refreshing paint, improving lighting, editing furnishings, addressing visible maintenance concerns and professionally staging the property.

The key is knowing which improvements will matter to buyers—and which projects are unlikely to produce a meaningful return.

Our team represented the sellers of four Colonial Acres homes during this 90-day period, with sale prices ranging from $850,000 to $1,830,000.

Those properties included a mature bungalow, a substantial family home and executive residences at the higher end of the market. This gave us direct, current insight into buyer behaviour across several Colonial Acres price ranges.

Two of the homes sold above asking within two days:

• 303 Castlefield Avenue sold for $1,810,000 after being listed at $1,599,900.
• 612 Stonebury Crescent sold for $1,525,000 after being listed at $1,495,000.

Both were strategically priced based on their condition, features and current competition—not artificially underpriced simply to create a sold-over-asking result. The sellers fully committed to the recommended preparation, staging, pricing, marketing and launch plans.

Our other recent Colonial Acres sales required different strategies because every property and seller’s circumstances were different. What remained consistent was the importance of understanding the competition, preparing carefully and positioning the home for the buyers most likely to appreciate it.

There is meaningful demand for the right Colonial Acres home, but a desirable address alone does not guarantee a quick or competitive sale.

Begin preparing before you are ready to list

Allow enough time to determine which repairs, improvements and presentation changes are worthwhile. Rushing to market before the property is ready can weaken the initial launch.

Compare your home with the right properties

A bungalow on a deep lot should not be valued in the same way as a newer executive home with a pool on an established crescent. The most relevant comparisons depend on lot, style, size, condition and features—not simply proximity.

Price for the current market

Overpricing to leave room for negotiation can reduce showing activity and cause buyers to question the property’s value. The first days of a listing often bring the greatest attention, and that opportunity can be difficult to recreate after a property sits or requires a price reduction.

Prepare for selective buyers

Buyers are noticing unfinished repairs, dated mechanical systems, poor presentation and renovation requirements. Not every concern needs to be corrected, but the price and marketing strategy must account for them.

Treat the launch as one coordinated plan

Preparation, staging, pricing, photography, video, marketing and timing should work together. The strongest results rarely come from treating these elements as separate or optional decisions.

The average sale price during the 90 days ending July 22, 2026 was approximately $1.24 million, while the median was $950,000.
The difference is significant because several luxury sales raised the average. Neither number should be used alone to estimate a specific home’s value.

Yes. Nine of the 21 firm or closed sales sold above their final asking prices.

However, 11 sold below asking, showing that multiple offers and above-list sales are not occurring equally across every price range or property type.

The median selling time was 17 days, but individual results ranged from immediate sales to more than four months.

Condition, pricing, competition and presentation all affect how quickly a property sells.

Not necessarily. Many sellers benefit more from selective repairs, paint, lighting improvements, editing and staging than from completing a major renovation.

A pre-listing consultation can help identify which improvements are likely to influence buyers and which ones may not be worth the cost or disruption.

Colonial Acres sale prices during this period ranged from the $700,000s to more than $2.6 million. A neighbourhood average cannot account for the differences between those properties—or accurately determine the value of your home.

Our confidential, property-specific market assessment will explain:

• Which recent sales are genuinely comparable
• What buyers would compare your home against today
• How your street, lot, layout, condition and renovations affect value
• Which preparation or improvements may be worthwhile
• How staging and presentation could influence the result
• The pricing, marketing and launch strategy we would recommend

Considering selling in Colonial Acres? Contact The Deutschmann Team for a confidential home valuation and customized selling strategy.

This report examines detached-home activity in Colonial Acres during the 90 days ending July 22, 2026. Active, conditional and pending listings reflect their MLS® status as of July 22. Pending transactions had firm agreements but had not yet closed. Listing statuses and sale details may change. Market statistics describe general activity and should not be used to determine the value of a specific property without a detailed assessment. Source: ITSO MLS® data.

The post Colonial Acres Waterloo Real Estate Market Update | July 2026 appeared first on Kitchener Waterloo Real Estate Agent - The Deutschmann Team.

♦

The plums we get in Ontario are, for the most part, either European or Japanese types, the latter actually Chinese in origin.

But whatever their origins, eat them now. I feel that summer is well and truly here — the heat and the sun — when yellow plums start to appear.

That appearance begins in July and August. Early freestone yellow plums called Early Golden are Ontario’s most prevalent plum, followed by semi-freestone cousin, the Shiro. In August moving into September, we will see the red and purple varieties at their best.

The Japanese and European plums, although millennia old in their native areas, were introduced to the New World as recently as the late 1800s. Plums are grown on every continent except Antarctica. We should also acknowledge that there is a long history of wild plums in Canada, eaten by our indigenous peoples.

As early as 1875, Luther Burbank took Chinese purple plums, which had been improved by Japanese breeders, and further developed them in the United States. The variety is known as the Burbank plum.

Plums are climacteric: that is, they can be harvested relatively green and allowed to ripen slowly. At home, ripen them at room temperature out of direct sunlight or in a loosely closed brown paper bag. They should then be refrigerated and eaten as soon as possible.

One medium-sized plum has about 36 calories and is a delicious source of Vitamin-C. Yellow plums are great for fresh eating, canning and cooking.

I find that my favourite yellow plums can be deceptive: their thick skin, when you press it, remains firm as if they are not yet ripe. But inside they can be just perfect.

So pay close attention to your yellow plums!

Plum compote recipe / Compote de prunes

Ingredients
3 cups yellow plums, stoned and quartered (sounds violent)
1/4 cup sugar
1 dash brandy
Juice of one medium-sized lemon
Spices like star anise, ground cloves as you like

Method
Peel plums and grate bit of lemon zest into them and mix. Combine ingredients in saucepan and bring to a gentle boil. Reduce heat and simmer for 10-15 minutes (depending on how firm your plums are). Serve warm or cold. Store well-sealed in the ice box for a few days.

Check out my latest post The yellow plums of summer from AndrewCoppolino.com.

  GHD have produced another report for public consumption . Like many of the rest it goes best with lots of sugar, artificial sweetener and or grease to help it slide down.  Perhaps money and self-interest are the very best forms of grease as they tend to ensure that alleged troublemakers, radicals and activists are ignored while bought and paid for intellectual prostitutes are given undue respect and credibility. The report is titled  "Lanxess Canada Municipal Aquifer Steady State Conditions Trial Report".

Basically the entire premise of the report is a croc. It is supposed to examine monitoring wells throughout the Elmira Aquifers to determine if there is significant "rebound" in contaminant concentrations AFTER  pumping in the Elmira aquifers has stopped. Well it never fully stopped as the major pumping well at the south end of Elmira (E7) continued pumping it's little heart out. There was also the somewhat embarassing issue with pumping well W5A located just south and west of the Lanxess site.  It kicked the bucket just BEFORE the so called pumping trial began. Oops! Also the number of monitoring wells and their location were not appropriate for what was supposed to be the rationale of the trial. No where near enough monitoring wells and all were located way too close to the pumping wells causing immediate drastic results either when the wells were shut down or when they were started up again.

As usual the maps/Figures supplied are too small for most eyes over 40 years old plus the text in attached Tables to them are even worse to read. Finally colour printers are required for those of us who no longer rate hard copies and must download tiny, coloured maps/Figures electronically. It's all a good way to thin out the field of critics. The analytical Tables provided could also have used two, vertical lines on each  showing when pumping was stopped and then restarted. It would have made the Tables more understandable.

Discussion and Conclusions are basically pathetic. There's a fair bit of jabber regarding anaerobic conditions, ORP (oxidation reduction), RPD (relative percent difference), ammonia, phosphates and nitrates plus DO (dissolved oxygen) that may excite biologists but not so much hydrogeologists. At least these big words make GHD look smart and help muddy the waters as probably intended.

Most importantly Lanxess, GHD and the MECP (Min. of Environment)   have scrupulously avoided the one word which must NOT be spoken, written or uttered upon excommunication from the Royal Order Of  Flamboyant  and Treasured Water Investigating Testifiers otherwise known as  ROOFTWITS. The magic word that they must not utter is     DNAPLS    . Under no circumstances they insist could either free phase or residual DNAPLS ever be the reason for high chlorobenzene concentrations or persistent chlorobenzene detections nearly thirty years after groundwater remediation by pump & treat has been ongoing. Oddly every other site with gross chlorobenzene and lots more chlorinated solvents contamination is recognized as a DNAPL site but here in Woolwich Township by the waving of magic wands and the intonation of non satanic chants; DNAPLS have been kept at bay. 

Thank God for their majesties Ken Seiling, Sandy Shantz and even Karen Redman.   

I started LeetCode again after a small break. I don’t know how many times I’ve restarted LeetCode.

This time, I decided to follow the NeetCode roadmap. It made learning LeetCode easier. It actually has structure and order. That made it easy to pick the next problem without thinking much.

I completed the following sections:

• Arrays & Hashing
• Two Pointers
• Sliding Window
• Stacks (recently completed)

After completing the sections, I looked at one of my accepted solutions and thought, “I know I solved this three days ago. Why can’t I explain why this line exists?”

Of course, I didn’t memorize the problems. I actually understood each one before moving on to the next problem.

So I decided to recollect everything from scratch. No hints.

I opened my notebook and started revising the sections I had completed.

Everything has an approach. I wanted one for revision too.

I wasn’t trying to invent new ideas. I just wanted to remember the old ones.

My approach was simple.

Just write.

Write everything.

• What were my initial thoughts?
• How did I solve the problem?
• How did I identify the logic?
• How did I eliminate the unnecessary work?
• How did I extract the optimized solution from the brute-force solution?

Write everything in simple English.

So I started writing every decision and every thought I had while solving that particular problem.

While solving, I only focused on getting the solution.

I just wrote the input and output, listed every approach I knew, and started solving.

I only cared about getting the problem accepted. My focus narrowed.

Once the problem was solved, my brain relaxed.

But during revision, I finally got to relax. I no longer had to search for an answer. Now I could ask why my reasoning worked.

That’s when I found something interesting. I wasn’t focused on getting to the solution quickly anymore. Instead, I became a reviewer and examined my own solution.

In this process, I repeatedly asked questions like:

• If that worked, why didn’t this?
• Why did this work?
• Why did I choose this data structure?
• Why did I make that decision?

While solving, every question was judged by one standard: “Will this get accepted?”

During revision, that pressure disappeared, and I finally started asking ‘why’ instead of ‘how’.

That created space for new ideas.

Voila.

I found ideas I hadn’t considered before.

I discovered new ways to solve the problem.

I understood the reasoning better and connected the dots.

That experience was incredible. I was in awe.

While revising, I remembered an essay I had read during my digital detox (which I eventually failed).

It was an essay by Paul Graham called Good Writing.

In Good Writing, he wrote:

This is only true of writing that’s used to develop ideas, though. It doesn’t apply when you have ideas in some other way and then write about them afterward.

It’s only when you’re writing to develop ideas that there’s such a close connection between the two senses of doing it well.

I remember thinking, “Is that really true?”

I thought, “Okay, let’s see.”

Then I moved on, like any other procrastinator.

I thought this kind of writing only helped people developing completely new ideas — essayists, philosophers, and researchers. Algorithms already felt finished to me. I thought writing was useful only when people were trying to discover something completely new.

I never imagined it would help while revising algorithms.

But during revision, I realized he was right.

This is what happened to me.

Yes, maybe you’ll find useless ideas.

A useless idea is still an idea.

Wrong ideas still teach you why the right idea is right.

You may not find the correct solution every time, but you’ll understand why one approach fails and another works. You’ll develop a much deeper understanding of the reasoning.

Sometimes, you even discover a better idea.

Either way, writing helps you walk away with something.

It made me wonder where else this way of writing could be useful.

Here are two questions I never asked while solving the problems but naturally asked while writing about them.

While solving it, I used prefix and suffix arrays. I calculated the suffix array on the go.

While writing about it, one question came to mind:

Why can’t I calculate the prefix on the go?

It turned out I could.

While solving it, I needed to calculate the number of replacements required. I calculated it using windowLength - maxFreq.

Here, maxFreq is the highest frequency of any character in the current window.

Then I wondered:

Why can’t I calculate minFreq instead?

minFreq would simply be the sum of all frequencies except the maximum one.

The answer was yes — but with a trade-off.

The idea worked, but it required another traversal, making it slower than the standard windowLength — maxFreq calculation, which is O(1).

let maxFreq = 0;

for (let freq of map.values()) {
    maxFreq = Math.max(maxFreq, freq);
}
let minFreq = 0;
let skippedMax = false;
for (let freq of map.values()) {
    if (!skippedMax && freq === maxFreq) {
        skippedMax = true;
        continue;
    }
    minFreq += freq;
}
if (minFreq <= k) {
    // valid window
}

Now compare that with the standard solution.

My approach

Find max       -> O(26)
Find minFreq   -> O(26)

Standard approach

Find max      ->  O(26)
windowLength - maxFreq  -> O(1)

The new idea wasn’t more optimal, but it made me understand why the standard solution was.

These pages hold more than solutions. They hold questions, failed ideas, better ideas, and conversations with my past self. Somewhere along the way, my notebook stopped being a revision notebook and became a place where I learned how to think.

I always thought revision was about remembering what I had already learned.

Instead, it became a conversation with my past self.

Sometimes I discovered better ideas.

Sometimes I simply understood why my original idea was already the right one.

Either way, I always walked away with a deeper understanding than when I started writing.

Thanks for reading.

Writing My LeetCode Solutions Changed How I Think was originally published in Code Like A Girl on Medium, where people are continuing the conversation by highlighting and responding to this story.

Visa Vulnerability Agentic Harness

Python 1.8k Updated Jul 3

Project N.O.M.A.D, is a self-contained, offline survival computer packed with critical tools, knowledge, and AI to keep you informed and empowered—…

TypeScript 35k Updated Jul 27

KITCHENER - It was a memorable Sunday for all the wrong reasons for the Kitchener Panthers.

The Panthers gave up 11 home runs to the league-leading Welland Jackfish in a 30-8 loss at Jack Couch Park.

The game got out of hand early, as Welland had 23 of its 30 runs on the board after the fourth inning, lighting up Panthers pitching and batting around the order in three straight innings.

Starter Owen MacNeil was yanked after recording just five outs, giving up 11 runs (eight earned) on six hits. He walked four in the loss.

Teodoro Ortega gave up two runs on six hits, but struck out eight in five innings of work for the win.

The bright spots for Kitchener came late, scoring six runs in the eighth inning, including home runs from Raffi Gross, Jackson Cooke, Trent Lawson and Petey Kiefer.

Kiefer was a single shy of hitting for the cycle.

The 38 runs scored in the game was a CBL season high, breaking the record of 37 scored in Kitchener's 23-14 win over Brantford on June 18.

Logan Grant had three home runs for the visitors. Ethan Mann, James Smibert and Justin Gideon all had two home run games.

Kitchener drops to 10-20 on the season. Welland improves to 22-10.

With the transaction deadline looming Monday, Kitchener sits seven games out of a playoff spot.

The Panthers are back at it Tuesday at home against Hamilton. First pitch is scheduled for 7:05 p.m.

GET YOUR TICKETS NOW and #PackTheJack!

TypeScript-to-Native Compiler

TypeScript 2k Updated Jul 28

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Zig 168 Updated Jul 28

One of the greatest resources for me when starting out was attending events or conferences hosted by senior engineers.

I used to and still watch many such conferences available on YouTube or attend them in person, as they helped me gain deeper insights into how things actually work. Be it Cloud, DevOps, Golang, or even Linux internals, these tech talks have always fascinated me.

While watching such videos, I would always think that someday I would also be giving a talk in front of many people and sharing my knowledge with them.

And honestly, that day wasn’t very far away. At the start of 2026 itself, in March, I got the opportunity to give a technical talk at Opstree Solutions.

The session was titled “Building CI/CD Pipelines for Infrastructure: From Automation to Testing.”

It focused on my ideas and perspectives based on the book Infrastructure as Code Dynamic Systems for the Cloud Age written by Kief Morris.

That book introduced some really interesting ways of looking at Infrastructure as Code. The point that intrigued me the most was how to test and implement a CI/CD pipeline for IaC, especially for provisioning code.

Although there were times while preparing for this talk when I couldn’t fully understand a few concepts, I now think I should have consulted a senior. But anyway, I searched online, and Reddit turned out to be a huge help. I also couldn’t complete the demo, which, in hindsight, should have been my highest priority.

Anyway, here are some lessons I learned from my experience and from watching the other speakers at several events:

Some people really struggle with this, and honestly, so do I. I get confused about what to say about myself. Well, that mainly depends on how well you know yourself. But when you’re starting out, you can simply say something like:

“Hey everyone, I’m Rajeshwari. I’m a freelance Cloud Engineer, and I love brewing coffee.” (Or not, if you actually don’t. 😄).

And that’s it. You don’t have to make it fancy.

This is probably the most important aspect of giving a talk. If you just keep talking and describing your slides, it starts feeling like a boring office meeting.

Instead, at regular intervals, ask the audience if they have any questions. Or even better, while introducing a topic, ask if someone already knows the answer before explaining it yourself. It naturally makes people more involved.

I wasn’t able to keep my audience as engaged as I wanted, but honestly, Sandeep sir made the session much more interactive by asking me thoughtful questions throughout the talk. It also helped me deepen my own understanding of the topic.

One drawback of my talk was that I couldn’t prepare the demo completely. As I mentioned earlier, there were a few concepts that I couldn’t fully grasp while preparing, which resulted in an incomplete demo, and I couldn’t present the code.

Thankfully, I had created a pipeline flow diagram as a backup and presented that instead.

Actually, I’d say prepare at all! I didn’t prepare the night before the talk or even 15 minutes before it. You already know the topic, and you’ve created the presentation, so why memorize everything? You can prepare a few key points that you want to cover, but don’t lock yourself into a script.

Just keep the conversation flowing while you’re on stage. I stayed calm and didn’t think much about the session beforehand. I was simply excited to attend the event itself. Trust me, it relieves a lot of pressure.

The point of a talk isn’t to show off your PowerPoint; it’s to show your understanding of the topic. For me, the best feeling is talking naturally, with ideas coming to my mind at that very moment instead of reading what’s written on the slides and explaining it again.

Even I couldn’t do this perfectly. Some of my slides were filled with too much text, and that definitely shouldn’t have happened.

So these were some of the lessons and experiences from that day.

The opportunity to give tech talks is one of the best things this field has given me. ❤️

Looking forward to many more such experiences!

And all the best for your first session!! 🙌🌟

Originally published at www.linkedin.com.

All about my very first technical talk was originally published in Code Like A Girl on Medium, where people are continuing the conversation by highlighting and responding to this story.

(Not a Medium paid member…no worries, read for free here)

You know the AI feature is done “right” when someone asks the obvious question and the room goes quiet.

What happens if we turn it off? (Not many have really planned for that)

Concepts like “backward compatibility” or “two-way door decision” have kinda lost their charm in the so-called “AI-first race”.

And even if teams treat “add AI” as a two-way door (reversible at any time) and build it that way, it's usually only in name.

In practice:

Once old system’s gone, it’s a one-way door wearing a two-way door’s reputation.

Behind every AI feature you can see, there used to be a boring system that just worked. Rules. If-this-then-that. Not exciting, but solid.

But as AI entered the picture, instead of standing alongside the old system, it stood atop it and pushed it out of the way.

And the boring (non-AI) version didn’t get kept. It got deleted.

So now the model is the system. And the day it hallucinates, or the API times out, or someone’s config drifts, there’s nothing behind it to catch the fall. Just the user, staring at whatever the model handed them.

The fix isn’t complicated. It’s just unfashionable because it means shipping the boring version first on purpose and treating it as permanent infrastructure, not a rough draft you throw away once the AI works.

Here’s the shape of it, using a plain example: a system that reviews a piece of text and flags issues before it ships (could be a support macro, a config file, a product description, doesn’t matter).

Step 1: Build the deterministic core (this is the system, not a placeholder for the system).

# core.py

def deterministic_review(text: str) -> dict:
    """
    Rule-based review. No AI. No external calls.
    This is the source of truth. Everything else is optional on top of it.
    """

issues = []

if len(text) < 20:
        issues.append("Content too short to be useful.")

if text.strip().endswith((".", "!", "?")) is False:
        issues.append("Missing terminal punctuation.")
        
banned_terms = ["TBD", "TODO", "placeholder"]
for term in banned_terms:
        
if term.lower() in text.lower():
        issues.append(f"Contains unresolved placeholder: '{term}'")

return {
        "source": "deterministic",
        "issues": issues,
        "passed": len(issues) == 0,
    }

Nothing clever here. That’s the point. This function will give you the same answer every time, forever, regardless of what any model provider does to their API next quarter. It’s not exciting. It’s load-bearing.

Step 2: The AI layer sits beside it (and not inside it).

# enhancer.py

import os
from openai import OpenAI

client = OpenAI()

def ai_review(text: str) -> dict:
    """
    AI-assisted review. Adds judgment the deterministic layer can't.
    Never the only line of defense. Never load-bearing on its own.
    """
    prompt = f"""
    Review the following content for clarity, tone, and ambiguity.
    Do not invent facts. Do not rewrite the content.
    Return a short list of specific concerns, or "No concerns" if none.

    Content:{text}
    """
    
response = client.chat.completions.create
    (
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": prompt}],
    temperature=0,
    )

return 
    {
    "source": "ai",
    "notes": response.choices[0].message.content.strip(),
    }

Notice what this function does not do. It doesn’t decide pass/fail. It doesn’t touch the original text. It doesn’t get called unless something upstream explicitly asks for it. It adds a second opinion. It never replaces the first one.

Step 3: The toggle (the focus point of this article).

# pipeline.py

from core import deterministic_review
from enhancer import ai_review

def review(text: str, use_ai: bool = None) -> dict:
    """
    The public entry point. Deterministic result is always computed
    and always returned. AI is additive, and fails safe.
    """
    use_ai = use_ai if use_ai is not None else os.getenv("USE_AI", "false").lower() == "true"

    result = deterministic_review(text)

    if not use_ai:
        return result

    try:
        ai_notes = ai_review(text)
        result["ai_notes"] = ai_notes["notes"]
    
    except Exception as e:
        # AI failed. The deterministic result is already computed and valid.
        # We log it, we don't crash, and we don't silently pretend AI ran.
        result["ai_notes"] = None
        result["ai_error"] = f"AI layer unavailable: {str(e)}"

    return result

Three things are true about this function that weren’t true about the “AI-as-the-feature” version most teams ship:

• The deterministic result is computed unconditionally, before AI is even considered. It’s not a fallback path bolted on after the fact. It’s the actual return value, every time, and AI either adds to it or doesn’t.
• The toggle is a real toggle. USE_AI=false doesn't mean "the AI feature is disabled and something is missing." It means the system runs exactly as it did before AI existed. Nothing degraded. Nothing broken. Just the version that was always there.
• Failure is visible, not silent. If the AI layer breaks, the response says so, explicitly, rather than quietly returning a worse answer and hoping nobody notices. ai_error is a field a caller can check. It's not swallowed by a bare except: pass.

Now here’s the thing about off switches important to remember.

You can’t add one retroactively, not really, not once a system has been live long enough that people have started trusting the AI-touched version as the version.

By the time something goes wrong, an “off switch” you build under pressure is really a panic button wired to a system that was never designed to run without the thing you’re now trying to remove. It’ll work, technically. It’ll also break three things you didn’t know depended on the AI layer being there.

The toggle in the code above costs almost nothing to build, if you build it on day one. It costs a full re-architecture to build after the fact, once “the AI version” has quietly become “the only version.”

So build the boring layer first. Keep it running underneath, permanently, not as a bootstrapping step you delete once the AI works. Let AI sit on top, opt-in, fail-safe, and honest about its own failures.

To conclude, I would say:

The real measure of whether a team understands AI governance isn’t whether they added guardrails.

It’s whether they could turn the AI off tomorrow, mid-incident, and still have a working system underneath.

Most teams, if they’re honest, would find out the hard way that they can’t.

Better to find that out in a design review than in production.

Thanks for reading this article; don’t forget to clap and follow ❤️

You can send me an invite @ LinkedIn or Substack 😎

Looking forward to connecting with you 🤝

You may also like to read:

• When RAG Fails, Look Beyond the Vector Database
• You Can’t Scale Content Without Scaling Its System!
• Your AI Agent Is Only as Confident as Your Least Confident Page

Trust Is a Toggle, Not a Feature: Why AI Should be Shipped With an Off Switch was originally published in Code Like A Girl on Medium, where people are continuing the conversation by highlighting and responding to this story.

♦

Masa harina: this ingredient is a foundational one for the many terrific Latin American restaurants — Salvadoran, Colombian and Mexican, for example — that are out there for us to enjoy.

You will find it in the food you eat their restaurant dining rooms and, in bags, on the shelves of the grocery store sections often found in these restaurants and small eateries. As such, these businesses are warm and casual community hubs that add much to the rich fabric of our food culture.

The word masa is “dough” in Spanish (masa harina is, literally, “dough flour”). It’s a traditional and key ingredient for Latin American cooking.

Taking sun- or fire-dried corn that’s been cooked and treated in lime water (calcium oxide), the soaked kernels are ground into a flour.

That flour is used to make the tortillas that make your wonderful tacos.

Check out my latest post Masa: dough at Latin American restaurants from AndrewCoppolino.com.

A batteries-included framework for building web apps

Rust 3.5k Updated Jul 28

Python 728 Updated Jul 27

First of all contrary to every credentialed sod and suit who have lost their credibility and integrity and agree with Lanxess Canada and the Ontario Min. of Environment that there is not any chlorobenzene in the Bedrock aquifer; I say this. Intellectual prostitution is no more glamorous than the real thing. In some aspects it is worse.

The reason that this lie suggesting that sure there is NDMA in the Bedrock Aquifer but not chlorobenzene is because NDMA is more easily dissolved and more easily pumped. It can be removed much easier from both aquifers and aquitards than chlorobenzene, a DNAPL chemical. Hence just as the leadership of APTE (Susan B. & Sylvia) were coopted in the early 1990s into becoming DNAPL deniers so both Uniroyal Chemical and the Ont. Min. of Environment (MOE/MECP) colluded in their October 1991 Agreement and November 4, 1991 Control Order to pretend that there were no free phase DNAPLS (Dense Non Aqueous Phase Liquids) either on the Uniroyal site or off their site having migrated into all the aquifers below the town of  Elmira. 

It is obvious to honest people with even a little bit of hydrogeological knowledge. Looking at the "Schematic Of Hydrogeologic Units Lanxess Canada Co." which are produced by Uniroyal/Crompton/Chemtura and now Lanxess over the last thirty-six years makes it very clear. These one page subsurface "maps"  are also known as Conceptual Site Models. From the top right corner showing the Creek ("Gig") and the UA (Upper Aquifer) one can follow the blue coloured aquifers downwards into the MU (Municipal Upper) then follow the blue MU leftwards (west & south) until it reaches more blue (marked LGR -low gamma resistivity) and descends further downwards into the ML (Municipal Lower) . From there moving to the right (i.e. north and a little east) one comes to the following FOUR wells all pumping NDMA, chlorobenzene and so much more namely W6A, W5A, W9 and W8. By the way there is also likely a window just to the right of W8 which corresponds to OW58 as stated in yesterday's Blog posting. It goes through the MAT (Municipal Aquitard) and connects the MU with the ML. 

Meanwhile and here's the kicker. THE BEDROCK AQUIFER IS DIRECTLY CONNECTED TO THE MUNICIPAL LOWER AQUIFER exactly where three of the four pumping wells (W5A, W6A, W9) well screens sit directly on top of the Bedrock. They are pumping both ML water and BR water albeit the free phase chlorobenzene (& more) DNAPL that gravity flowed into this location are from either or both the north-east window (near OW58) or from the south-west window (near W4, OW57-32R, Howard St. water tower); is likely long gone into the fissures and cracks of the fractured Bedrock Aquifer. There could be some free phase DNAPL still left in the ML or not but certainly that which is into the Bedrock Aquifer is there forever. 

This is but part of the coverup, collusion and corruption between Uniroyal Chemical and the Ontario Ministry of Environment (MECP). Surviving APTE members may some day be able to figure out how early on their leadership betrayed them. Or not. Time will tell.     

HAMILTON - The Kitchener Panthers offence hit a brick wall Friday night in Hamilton.

The Panthers garnered just four hits all night in what was a 13-1 loss to the Cardinals.

Two of the four came in the first inning, but they weren't able to get anyone across. Meantime, Hamilton scored four runs in the first to establish a lead they wouldn't relinquish.

Yosvani Penalver, Malik Williams, Raffi Gross and Josh Williams got the four hits.

The lone Panther run came in the fifth when newcomer Jackson Cooke grounded out, allowing Gross to score.

Dionys Rodriguez gave up eight runs on nine hits in 4.1 innings in the loss. He struck out six and walked one.

Kitchener has lost three straight and is 10-18 on the year. Hamilton improves to 17-9.

The Panthers continue its busy weekend Saturday at 4:08 p.m. in Barrie.

Then, they host Welland Sunday at 5 p.m.

GET YOUR TICKETS NOW and #PackTheJack!

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TypeScript 43.4k 1 issue needs help Updated Jul 26

remark plugin to support GFM (autolink literals, footnotes, strikethrough, tables, tasklists)

JavaScript 1.2k Updated Feb 10, 2025

You know most children by the age of six or seven have learned that lying usually only makes things worse. Statements like the dog did it or the baby did it rarely fly with parents. Unfortunately as a society we have learned to condone dishonesty in many forms. 

Yesterday's July 23, 2026 report by GHD sent to the Min. of Environment (MECP) and titled "Municipal Aquifer Steady State Conditions Trial" is an example of what my Blog title is all about. I understand that exceptions to the fibbing rule exist which include two dishonest parties sending knowingly false information back and forth in order to reinforce their agreed upon self-serving "truths". No one is offended because both parties have long ago agreed to the deception. Examples abound such as President Bush lying about Iraq's Weapons of Mass Destruction (WMD). England and the U.S. needed some justification for attacking Iraq so they jointly made sh*#  up. Countries do it, individuals do it and polluting corporations do it. 

There are a host of made up falsehoods regarding the Elmira Water Crisis.  Only a very few to date have been debunked or admitted to such as Allan Deal (GHD) admitting to TRAC that Varnicolor Chemical contributed chlorinated solvents to the Elmira drinking water aquifers (MA) as per the Minutes of their September 12, 2024 meeting in Council Chambers. This was on page 7 and on page 6 of these Minutes is also finally the admission of DNAPL existing near pumping well W4 by the Howard St. Water Tower and beside monitoring well OW57-32R. 

The page 6 admission regarding off-site DNAPL presence is important in the context of yesterday's  report as it clarifies why Figures 5 & 7 clearly show both the remaining Municipal Upper and Municipal Lower Aquifer locations of chlorobenzene in Elmira's subsurface. They are located  to the immediate east of former pumping well W4 as well as of monitoring wells OW57-32R and OW57-38 . The remaining plumes in both aquifers (MU, ML) are directly beneath the former Varnicolor Chemical site with Howard Ave. on their south side and First Ave on their north side. Both plumes cross under Union St. as they are slowly pulled towards pumping wells W5A/B in each aquifer. Also of interest in yesterday's report is the statement on page 15 in the Conclusions that  "GHD notes that extraction wells were drilled in the core of the existing plumes at the time of installation.". This explains the location of pumping well W4 beside the free phase DNAPL clearly discovered prior to the startup of the off-site pumping in August 1998 but denied originally at a CPAC meeting around 2004-5 when I presented a writeup about it found in a monthly Progress Report. It was then denied repeatedly for years until the admission of its' presence at the September 12, 2024 TRAC meeting. 

DNAPLS (chlorobenzene & more) left the Uniroyal Chemical site decades ago in at least two locations ending up by the Howard St. Water Tower and by monitoring well OW58-24 on the property line with Nutrite/Yara via a "window" through the Municipal Aquitard.  Both Uniroyal and the Ontario M.O.E. colluded to hide and deny this fact from the public in order to preserve their sweetheart deal which covered up the Ministry's negligence and incompetence and which reduced Uniroyal's cleanup costs by millions of dollars. 

Sorry for the upset and disruption to thin skinned individuals at Woolwich Township who insist on playing nice with those who don't play nice, much less legally. 

July 21, 2026, was Black Women’s Equal Pay Day here in the U.S. It’s a symbolic date that marks how far a Black woman must work into the current year to make the same amount that a white, non-Hispanic man earned last year.

Another way to look at it? Imagine finding out you’ve been earning just 65 cents for every dollar paid to a coworker. That’s the current wage gap for Black women working full-time, year-round in the U.S.

And there are more equal pay day milestones coming up, each revealing deep disparities:

• Moms’ Equal Pay Day — August 6
• Native Hawaiian and Pacific Islander Women’s Equal Pay Day — September 15
• Latina Equal Pay Day — October 8
• Disabled Women’s Equal Pay Day — October 20
• Native Women’s Equal Pay Day — November 19

While I hope your organization conducts regular pay equity reviews and addresses any inequities, there’s also something we can do on a personal level: Discuss our compensation.

It’s uncomfortable territory for many of us, but when we tell others what we make, we provide them with valuable data points. And data is a helpful tool in any negotiation process.

Share this action on Instagram, LinkedIn, or YouTube.

Should employees and job candidates have to use their own credit card for business travel and other expenses?

Paolo Gaudiano and Cynthia Overton argue in their new book Meritocracy that this common workplace practice is one of many that quietly undermine merit.

They explain that structural enablers and organizational biases prevent meritocracy all around us. For example:

• The enabler: The organization requires individuals to pay business travel costs upfront and request a reimbursement later.
• The bias: This creates bias among employees at different socioeconomic positions. Not everyone can float hundreds — or thousands — of dollars in company expenses. Some people don’t have a credit card. Others have low credit limits or can’t afford to carry the balance while waiting weeks for reimbursement.
• The solution: Hire a company travel agent, provide corporate credit cards paid by accounting, give cash advances.

If someone needs to travel or make purchases for work, don’t assume they can “just put it on their credit card.” Instead, provide another option.

For example, use virtual credit cards (VCCs) or temporary prepaid corporate cards, available from many financial institutions. They allow your business to instantly issue temporary 16-digit card numbers for specific trips, set firm spending limits, and restrict charges to travel categories such as flights and hotels.

“It’s taking longer because the decision maker is older and more cautious.”

I heard a leader make this comment during a recent virtual meeting.

My first instinct was to let it go. I had another meeting starting soon. This leader was someone I respected. He was thoughtful and empathetic. Maybe it wasn’t worth bringing up.

But I try to practice what I preach.

So, as the call was wrapping up, I asked the leader if he could stay on the line for a few more minutes because I had something I wanted to share with him.

After everyone else left, I said, “I hope you’re open to some feedback” and then summarized what I had heard him say. I pointed out that he had reinforced a negative stereotype about older people, and that while I didn’t think he meant any harm, he sent a subtle message to others on that call that it’s okay to assume older folks are going to be slower and more cautious with decision-making or other aspects of their job.

I added, “You could simply have said the decision was taking longer than expected, without attributing it to their age.”

He nodded in agreement and sincerely thanked me for the feedback.

It reminded me that these conversations don’t have to be confrontational. A respectful conversation after the meeting can be enough to help someone notice a stereotype they hadn’t realized they were reinforcing.

I hope you’ll do the same the next time you witness one.

Last week, the US Defense Secretary Pete Hegseth mandated testing testosterone levels for service members over 30 and recommended hormone therapy if needed. Afterward, Fox News host Jesse Watters made an awful joke on air about it. He chuckled, saying,

“Women on base: you better be careful. Port calls, women in Asia: you better be careful. Because these guys are going to be wild animals, and you better watch out.”

Sexual violence is not something to joke about.

And as I shared in a previous newsletter, research shows that when someone tells a denigrating joke, it signals that behavior is acceptable. People who might normally conceal their feelings feel freer to express them.

As better allies, let’s speak up. For example, “We don’t joke about rape here.”

A subscriber from Berlin wrote to tell me about something she’s been noticing on public transportation: there’s a general lack of awareness of people with disabilities and access needs.

Here are some examples she regularly sees:

• A blind person navigating roads, using the markings for blind people, which are fully occupied by people walking with rolling suitcases.
• A parent juggling a stroller, a child, and shopping bags, with no one offering their seat or making space for the stroller.
• A wheelchair user trying to navigate a crowded train, weaving around bags and feet that never move because no one looks up.

She urges all of us to, “Look up and be aware of your surroundings so you’re able to offer help in situations where it’s needed.”

Most people are perfectly capable of managing on their own. But knowing someone noticed and cared enough to make space or ask how they might help can make all the difference.

🙏

If you’ve taken a step towards being a better ally, please reply to this email and tell me about it. And mention if I can quote you by name or credit you anonymously in an upcoming newsletter.

That’s all for this week. I’m glad you’re on this journey with me,

Karen Catlin (she/her), Author of the Better Allies® book series

Copyright © 2026 Karen Catlin. All rights reserved.

Together, we can make a difference with the Better Allies® approach.

• Say thanks to Karen and buy her a coffee ☕ (Need a receipt for educational reimbursement? Reply to this email, and we’ll take care of it.)
• Sponsor an edition of this newsletter
• Follow @BetterAllies on Instagram, Medium, or YouTube. Or follow Karen Catlin on LinkedIn
• Read the Better Allies books
• Tell someone about these resources

Break the Silence Around Compensation, and Other Actions for Allies was originally published in Code Like A Girl on Medium, where people are continuing the conversation by highlighting and responding to this story.

KITCHENER - On K-W Oktoberfest night, the Berlin Kegtappers and Toronto Maple Leafs played through more twists and turns than a pretzel.

But in the end, the Leafs emerged victorious 9-3 at Jack Couch Park Thursday night.

It didn't start pretty for Berlin starter Jorge Minyety, who gave up a solo shot to Brando Leroux on the fourth pitch of the game.

It was the first of two home runs on the night for Leroux.

He broke open what was a 5-3 Leaf lead in the eighth with a two-run shot in what was an otherwise nail biter of a game.

Minyety struck out seven and gave up four runs (two earned) on seven hits in six innings of work.

The story of the game became the errors that led to runs being scored.

A wild pick-off attempt off the glove of Yosuke Fujie at third allowed Toronto's second run to score in the first inning. 

Fujie redeemed himself later with a pair of spectacular defensive plays at third, and hit a solo home run to make it 4-3 in the sixth inning.

In the eighth, Crix Taveras was caught in no man's land between first and second, but a throwing error and attention away from Yordan Manduley allowed the former Panther to come in to score.

Marcus Knecht hit a two-run homer in the ninth inning to round out the scoring.

Kitchener drops to 10-17 on the season, while Toronto improves to 9-18.

Kitchener is on the road in Hamilton Friday, Barrie Saturday and back home Sunday to take on Welland at 5:05 p.m.

It begins a tough stretch for the Panthers, who play their next seven games against opponents currently in playoff positions.

GET YOUR TICKETS NOW and #PackTheJack!

This is but one of the retreaded wellfields that Waterloo Region are reopening in their desperation to keep builders and developers happy. Don't worry they do the risk calculations and theoretically at least while your risk of getting cancer will certainly rise with all these contaminated aquifers being put back in service; the numbers may be tiny such as an increase from 2 or 3 "excess" cancers in a million to a marginally greater 4 "excess" cancers in a million. No worries there especially as hardly any of us have friends, colleagues or relatives suffering cancers, past cancers or fatal cancers. Right?

 The Greenbrook Wellfield wells, K1, K2, K4B, K5A and K8 located near Homer Watson Blvd. and Stirling Ave. in Kitchener were all on standby status from at least 2003 until 2007. Newspaper accounts also advise us that that situation has continued during the 2020s whether from a chlorine/ammonia screwup and explosion or from the 1,4 dioxane contamination that came from the Ottawa St. Landfill. Now there have also been well redrills and replacements in this wellfield as the current wells are now known as K1A, K2A, K4C, K5A and K8.  These machinations if you will are common practice for the Region when they have "problematic" wells and examples in Cambridge for example include drilling past and through a contaminated zone of a well in order to pump water from a deeper less contaminated or uncontaminated zone.   

It is my opinion that this Grand River Source Protection Area Assessment Report Chapter 8, July 29, 2025 is unnecessarily thick and inflated with data that is at best filler or meant to make reading difficult and tedious. That said with enough patience and tenacity and overall knowledge a serious person can find much to be concerned with regarding this wellfield. Firstly the chances of 1,4 dioxane being the only toxic contaminant to reach the Greenbrook Wellfield from the Ottawa St. Landfill is somewhere between zero and nil. Look for benzene, chlorinated solvents and all the usual array of industrial solvents that were dumped there including by Elmira industries such as Varnicolor Chemical and if I might hazard a guess probably Uniroyal Chemical as well back in the day. Paper restrictions were strong whereas physical restrictions were not.

Other issues include high chlorides and high sodiums maybe from road salt but also common from industrially contaminated aquifers. Also I should applaud at least a couple of the Figures in this report as they do identify the Total Number of Significant Threat Activities as well as the Total Number of Properties with Significant Threats. Those numbers are huge (630, 379). They also indicate both High Unadjusted Intrinsic Vulnerability levels for this wellfield as well as High Adjusted Intrinsic Vulnerability threats to water quality. 

Waterloo Region are desperate to keep the water flowing and in my opinion they are risking your and my health for their own benefit. What else is new when it comes to water protection. 

The lazier way to manage everything docker

Go 52.2k Updated Apr 19

Mars needs allies, intelligence and time.
Only blood and fire can earn them all three.

Read Alien Olympus in ebook, audiobook or paperback now!

♦

Despite sacrifices and even victories, the Protectorate of the Mage-Queen of Mars is losing the war against the Reezh Kazh, the fascist theocracy that rules the only aliens they’ve ever met.

Ambassador Connor O’Hannagain has been sent to find allies among the reezh home worlds, the old and mighty systems that defied the Kazh once—but a centuries-long cold war has left the enemies of his enemy paranoid and violent.

Mike Kelzin, husband, pilot and spy, is the Protectorate’s eyes and ears, seeking every scrap of intelligence that can be found on the Kazh. But access to the enemy worlds is nigh impossible, leaving his best chances in the occupied Chimera System—where even the Resistance is entirely cut off from Mars.

Mage-Admiral Jane Alexander, Crown Princess and fleet commander, knows that they need time more than anything else. Time their enemy is unlikely to give them.

To turn the tide, Mars must buy allies, intelligence, and time—and only the oldest currency can pay for all three.

Blood.

The post Alien Olympus is out now! appeared first on Glynn Stewart.

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Python library for generating ambient music from text descriptions. No GPU required. Turn text into sound with a single line of code.

Python 41 Updated May 29

What does your life look like when you are living at your courageous best?

That question came from a leadership coach during a women’s leadership program I was part of at work. The room went quiet, then people started naming their fears. Talking to a large audience. Doing something new outside their comfort zone. Networking with unknown people.

I sat there realizing I did not share any of those fears. Mine was self-advocacy.

For years my mantra was to let the work speak for itself. It felt like the safer, more dignified choice. But in a world of shrinking attention spans, is it fair to expect someone else to notice what I built? That question sent me into a why-why analysis on what I was missing.

Two problems surfaced immediately. Firstly, I do not always know what I should be advocating for. I do the work, but I rarely stop to name what it proves about me. Moreover, even when I know what to say, I do not know how to say it without sounding like I am bragging.

And I am living this right now. I led a product build that went from zero to one with a successful beta run in three months. We are now moving towards general availability. Scaling it from here on needs more people on my team. But when I raise this with my leaders, I can see they do not instinctively get why.

Because I never told them what it actually took to get here. I never walked them through the build, the partner negotiations, the scaling decisions, the ongoing support, all of it stacked on top of each other for months. I assumed the beta success would speak for the effort behind it. It did not. Success is visible. The work underneath it is not, unless you name it.

This article is my attempt to work through both, using what I learned in the session and what I have tested since.

Self-advocacy begins with self-trust, and self-trust is shakier than it looks.

Every evening a voice shows up and tells me the day did not amount to much. It does not pause to check; it just delivers the verdict. I used to treat that voice as the final word.

But there is a second voice, if I actually let it speak. It does not argue with the critic directly. It just asks one question first. What did I actually get done today? Most evenings, when I stop and answer that honestly, the list is longer than the critic gave me credit for. The day was not wasted. I simply never stopped to notice it before moving on to the next thing.

Call it the critic and the mentor. The critic is fast and loud. It shows up uninvited every single day. The mentor only speaks if you deliberately ask it a question, which is exactly why it loses so often.

Here is the fix I am using. Every time the critic makes a claim, I call in the mentor to check it against evidence, not feeling.

And evidence comes in two forms. Functional evidence talks about what I actually produced. That is a fact, not a feeling, and it directly counters the critic's claim. Emotional evidence involves what I got through. Moments I stayed steady, or recovered from something hard.

The reason self-trust feels shaky is not that the evidence does not exist. It is that we never log it. The critic keeps a precise record of every shortfall. The mentor gets no record at all, unless you build one.

So the practical answer to problem one is simple. Keep a running log, even three lines a week, split into two columns. What did I produce. What did I get through. That log becomes the material your mentor uses to talk back to the critic. It is also, directly, the raw material for what you advocate for later.

Knowing your evidence is only half the problem. The other half is saying it out loud without it sounding like self-promotion.

Here is the distinction that unlocked this for me. Self-advocacy is stating a fact. Self-promotion is trying to win approval. The two get confused because they can use the same words. The difference is in what you attach to the sentence.

If I say, I turned around this initiative despite the constraints, and stop there, that is advocacy. It is a fact, stated plainly, with no ask attached.

If I add, so I hope people notice, or, so I deserve more credit, that same sentence turns into a request for approval, and it starts to feel uncomfortable to say, and to hear.

The technique is to separate the update from the ask. State what happened. Do not hedge it with a joke, do not shrink it with a qualifier, do not attach a request unless you actually have one. If you do have an ask, make it separately, and make it direct.

In practice, this sounds like: This shipped, and it took solving three specific constraints. Not: I don’t know if this matters, but I guess I managed to get this out despite everything. The first is advocacy. The second is an apology wearing the clothes of an update.

Self-advocacy is not one skill. It is knowing what to say, built from evidence you deliberately collect, and knowing how to say it, built from separating fact from request.

1. Log your evidence weekly, split into what you produced and what you got through.
2. When the critic speaks, ask what the mentor would say, using the log as proof, not opinion.
3. When you communicate an update, state the fact plainly, with no self-deprecating qualifier and no unstated ask.
4. If you have an actual request, make it as its own sentence, separate from the update.

I turned this log into a skill called daily self-advocacy log, open source on GitHub: github.com/kaantibshetty/skills-library/tree/main/career/daily-self-advocacy-log. You can schedule a task using this skill on Claude Cowork or Perplexity, and it will auto-trigger a conversation at the end of your day. Each evening it asks two questions: what did you produce and what did you get through, then saves the entry to a running log so the mentor always has evidence on hand.

The courageous version of me is not the one who talks the loudest about her work. It is the one who keeps the receipts and hands them over without apologizing for it.

The Courage Nobody Talks About was originally published in Code Like A Girl on Medium, where people are continuing the conversation by highlighting and responding to this story.