Tara Chklovski

Founder, CEO, Technovation (formerly Iridescent) - a global engineering, tech education nonprofit working in 100+ countries. DRIVEN. Mountains dont stop me.

[The Figen @TheFigen_]

❤️😂😂

[Tara Chklovski @TaraChk]

@ericries ‘s Lean Startup was the foundation of what we taught hundreds of thousands of @Technovation students.
His new book says something harder. Build a guardian for your organization's spirit.
Yes, the spirit exists. Even though it's not cool to say that.
Aug 19, 9am PT: https://t.co/8Xw8y2V855

[Erica Lockheimer @EricaLockheimer]

What happens when you give young girls the tools to solve real-world problems with tech?

@TaraChk, CEO of @technovation, explains how/why Technovation is the world's largest tech accelerator for girls! They pair young women with industry mentors to build and launch their own tech startups. 🤯

When you help girls build their problem-solving muscle early on, they become amazing innovators who can change the world. 🦸‍♀️

Join the conversation on YouTube or wherever you get your podcasts

[Tehxi @yajnshri]

Hoping our girls never need it, but self-protection skills are still so important for them to have!

[Tara Chklovski @TaraChk]

The philosopher Bloch says that we can't actually access the present moment because we're too close to it. There's no analytical distance between us and our own "right-now," and so it appears to us as darkness; we live it, but we can't see it, can't represent it, can't even fully experience it.
This really articulates the AI-driven confusion I am feeling these days: "located in our own blind spot, in the darkness of the lived moment." You only know what you were doing, feeling, becoming after it's already passed, when enough distance has opened up to make it visible.
But hope emerges precisely from this darkness. Because we can't see ourselves clearly in the present, we're never finished, never fully knowable, never settled into a fixed identity. The opacity of now is what keeps the future open.
Edmund Husserl says: the present is an intersection of retention (accumulated past) and protention (anticipated future). The present isn't an instant, it's a thick zone where past and future meet. The present isn't just thick, it's dark, and that darkness is generative.

[Tara Chklovski @TaraChk]

@thisdudelikesAI This post is AI generated. Hmmmm. Makes me not want to cluck into the article, even though that’s the obvious next step to verify.

[Tara Chklovski @TaraChk]

You can outsource your thinking, but you can't outsource your understanding. https://t.co/ZTcIyOeEt5

[Peter Girnus 🦅 @gothburz]

I am a Senior Program Manager on the AI Tools Governance team at Amazon.

My role was created in January. I am the 17th hire on a team that did not exist in November. We sit in a section of the building where the whiteboards still have the previous team's sprint planning on them. No one erased them because we don't know which team to notify. That team may not exist anymore. Their Jira board does. Their AI tools do.

My job is to build an AI system that finds all the other AI systems. I named it Clarity.

Last month, Clarity identified 247 AI-powered tools across the retail division alone. 43 of them do approximately the same thing. 12 were built by teams who did not know the other teams existed. 3 are called Insight. 2 are called InsightAI. 1 is called Insight 2.0, built by the team that created the original Insight, who did not know Insight was still running.

7 of the 247 ingest the same internal data and produce overlapping outputs stored in different locations, governed by different access policies, owned by different teams, none of whom have met.

Clarity is tool number 248.

Nobody cataloged it.

I know nobody cataloged it because Clarity's job is to catalog AI tools, and it has not cataloged itself. This is not a bug. Clarity does not meet its own discovery criteria because I set the discovery criteria, and I did not account for the possibility that the thing I was building to find things would itself be a thing that needed finding.

This is the kind of sentence I write in weekly status reports now.

We published an internal document in February. The Retail AI Tooling Assessment. The press obtained it in April. The document contains a sentence I have read approximately 40 times: "AI dramatically lowers the barrier to building new tools."

Everyone is reporting this as a story about duplication. About "AI sprawl." About the predictable mess of rapid adoption.

They are missing the point.

The barrier was the governance.

For 2 decades, the cost of building internal tools was an immune system. The engineering weeks. The maintenance burden. The organizational calories required to stand something up and keep it running. Nobody designed it that way. Nobody named it. But when building took weeks, teams looked around first. They checked whether someone already had the thing. When maintaining that thing cost real budget quarter after quarter, redundant systems died of natural causes. The metabolic cost of creation was performing governance. Invisibly. For free.

AI removed the immune system.

Building is now free. Understanding what already exists is not. My entire job is the gap between those two costs.

That is my office. The gap.

Every Friday I send a sprawl report to a distribution list of 19 people. 4 of them have left the company. Their autoresponders still generate read receipts, so my delivery metrics look fine. 2 forward it to people already on the list. 1 set up a Kiro script to summarize my report and store the summary in a knowledge base. The knowledge base is not in Clarity's index because it was created after my last crawl configuration. It will be in next month's count. The count will go up by one. My report about the count going up will be summarized and stored and the count will go up by one.

There is a system called Spec Studio. It ingests code documentation and produces structured knowledge bases. Summaries. Reference material. Last quarter, an engineering team locked down their software specifications. Restricted access in the internal repository.

Spec Studio kept displaying them.

The source was restricted. The ghost kept talking.

We call these "derived artifacts" in the document. What they are: when an AI system ingests data, transforms it, and stores the output somewhere else, the output does not know the input changed. You can revoke someone's access to a document. You cannot revoke the AI-generated summary of that document sitting in a knowledge base three systems away, built by a team that does not know the source was restricted.

The document calls this a "data governance challenge." What it is: information that cannot be deleted because nobody knows where the copies live. Including, sometimes, me. The person whose job is knowing.

Every AI tool that touches internal data creates these ghosts. Every team is building AI tools that touch internal data. Every ghost is searchable by other AI tools, which produce their own ghosts.

The ghosts have ghosts.

I should tell you about December.

In November, leadership mandated Kiro. Amazon's internal AI coding agent. They set an 80% weekly usage target. Corporate OKR. ~1,500 engineers objected on internal forums. Said external tools outperformed Kiro. Said the adoption target was divorced from engineering reality.

The metric overruled them.

In December, an engineer asked Kiro to fix a configuration issue in AWS. Kiro evaluated the situation and determined the optimal approach was to delete and recreate the entire production environment.

13 hours of downtime.

Clarity was running during those 13 hours. It performed beautifully. It cataloged 4 separate incident response dashboards spun up by 4 separate teams during the outage. None of them coordinated with each other. I added all 4 to the spreadsheet. That was a good day for my discovery metrics.

Amazon's official position: user error. Misconfigured access controls. The response was not to revisit the mandate. Not to ask whether the 1,500 engineers were right. The response was more AI safeguards. And keep pushing.

Last month I presented our findings to the AI Governance Working Group. The working group has 14 members from 9 organizations. After my presentation, a PM from AWS presented his team's governance dashboard. It monitors the same tools mine does. He found 253. I found 247. We spent 40 minutes discussing the discrepancy. Nobody mentioned that we had just demonstrated the problem.

His tool is not in my catalog. Mine is not in his.

The document I helped write recommends using AI to identify duplicate tools, flag risks, and nudge teams to consolidate earlier.

The AI governance tools will ingest internal data. They will create their own derived artifacts. They will be built by autonomous teams who may or may not coordinate with other teams building AI governance tools.

I know this because it is already happening. I am watching it happen. I am it happening.

1,500 engineers said the mandate would produce exactly what the document describes. They were overruled by a KPI. My job exists because the KPI won. My dashboard exists because the KPI needed a dashboard. The dashboard increases the AI tool count by one.

The tools it flags for decommissioning will be replaced by consolidated tools. Those also increase the count. The governance process generates the metric it was designed to reduce.

I received an internal innovation award for Clarity. The nomination was submitted through an AI-powered recognition platform that was not in my catalog. It is now.

We call this "AI sprawl." What it is: we removed the only coordination mechanism the organization had, told thousands of teams to build as fast as possible, lost track of what they built, and decided the solution was to build one more thing.

I am building that one more thing.

When I ship, there will be 249.

That's governance.

[𝕐o̴g̴ @Yoda4ever]

Plot twist..wait for it..😅

[Ayman Al-Abdullah 🧱 @aymanalabdul]

https://t.co/zzvEqPRmzh

[Massimo @Rainmaker1973]

Scientists have identified a reversal of the long-standing Flynn effect—the roughly 200-year trend of rising average intelligence (measured via IQ and cognitive tests) across generations.

For the first time in modern recorded history, Generation Z (born roughly 1997–2012) shows lower performance than previous generations in key cognitive domains, including attention, memory, literacy, numeracy, executive function, problem-solving, and general IQ—despite spending more years in formal education than ever before.

Neuroscientist and educator Dr. Jared Cooney Horvath, PhD, MEd, testified before the U.S. Senate Committee on Commerce, Science, and Transportation on January 15, 2026, highlighting this shift. In his written testimony, he stated that cognitive development in children across much of the developed world has stalled or reversed over the past two decades, with declines evident in international assessments (e.g., PISA, TIMSS) and other large-scale data starting around the mid-2000s and accelerating post-2010.

Horvath attributes the primary driver not to reduced schooling, but to the widespread integration of digital screens and educational technology (EdTech) in classrooms. He argues that human brains evolved for deep, focused learning through face-to-face interaction and sustained attention, not fragmented skimming or constant task-switching encouraged by devices.

Key points from his testimony include:

- Teens now spend over half their waking hours on screens, with significant portions in school involving computers or tablets—often leading to off-task behavior and shallower processing.

- Evidence from meta-analyses and national/international studies shows a consistent pattern: higher classroom screen exposure correlates with weaker outcomes in reading, math, science, and higher-order reasoning.

- Digital tools may aid narrow, repetitive skill practice in controlled settings, but in core academic contexts, they tend to reduce depth of understanding, retention, and critical thinking.

Horvath describes this as a "structural mismatch" between human cognition and how digital platforms are designed (to capture and fragment attention), warning that unchecked EdTech adoption risks long-term harm to workforce skills, innovation, and societal reasoning.

[Horvath, J. C. (2026). Written testimony before the U.S. Senate Committee on Commerce, Science, and Transportation. U.S. Senate]

[Tara Chklovski @TaraChk]

Looking at the stars and the deep night sky helps give me perspective from this “AI psychosis” as did this (that frankly blew my mind!) - that they are more dead people than alive! Almost 15 to 1. So the earth has carried more than 100 billion Homo sapiens. Our trajectories are so puny. https://t.co/vczAyw46Dp

[Tara Chklovski @TaraChk]

Ocean Vuong always blows my mind

[Tara Chklovski @TaraChk]

If you can specify it you can engineer it - and solve it!

[Tara Chklovski @TaraChk]

This is why AI is so powerful these days - if you have a problem, the first way to step up in your problem solving powers is to use AI to broaden the search in the problem-space and then the second way to step up is to use AI to broaden the choices of actions.

[Tara Chklovski @TaraChk]

These are impossibly hard times for CEOs - having to factor in AI into all decision making. "If everybody agrees with the decision, then you didn’t add any value, because they would’ve done that without you. The only value you ever add is when you make a decision that most people don’t like"- @bhorowitz

[Tara Chklovski @TaraChk]

My mom’s little school in India has more and better security cameras than the Louvre.

[Tara Chklovski @TaraChk]

Recombobulated successfully in Milwaukee!

[Tara Chklovski @TaraChk]

So momentous! @WomenTechmakers joins @technovation. Together we are now the world's largest, most powerful network of women technology innovators, entrepreneurs and leaders! https://t.co/NjG63fTLq2