Matt Olson

Optimist · truth seeker · builder

[Matt Olson @ahbiscuits]

@samlambert @NickVanWig My man

[Matt Olson @ahbiscuits]

This internal side project became so useful we decided to share it more broadly. Check it out!

[Michael Grinich @grinich]

Today we’re launching Atlas, an AI teammate that works alongside your team in Slack.

It answers questions, takes action, and learns how your company works.

Read more and try it today: https://t.co/wnCpmyiYSR

[Lenny Rachitsky @lennysan]

My biggest takeaways from @Netflix's Chief Product and Technology Officer Elizabeth Stone:

1. Elizabeth believes that “systems thinking” is becoming the most important skill in the AI era. In engineering and product, this means people who can see across business domains and build the common capabilities that let many teams move quickly. In design, it means experience designers who create templates and design systems so that non-designers can ship work that stays coherent and on-brand. The underlying driver is velocity: when more people are doing more types of work at higher speed, you need to be good at building common scaffolding.

2. Systems thinking is learnable: zoom out one level from your specific problem. Given a task, step back one click—what bigger problem does this serve the business, will it scale across the product surface areas, should it become a platform capability? The companion habit: do your job in a way that helps your manager do theirs. This will force you to think about how all the pieces fit together.

3. Expect a storming phase before a forming phase. The role confusion people feel right now (“What is my job anymore?”) is the predictable middle of any transformative technology. Elizabeth’s advice: focus on high-quality source-of-truth data, guardrails on what ships, and constant internal reinforcement that humans own what they create.

4. The top AI labs converged on Netflix’s culture. High agency, high talent density, top-of-market pay, bottom-up thinking, fast experiments—the traits Lenny hears constantly from AI labs were in Netflix’s early culture deck. Elizabeth’s explanation: excellence comes from hiring exceptional people, trusting them to do great work, and holding them accountable.

5. Netflix’s culture is centered around building “excellence as an operating system.” High talent density, radical transparency, context not control, and the keeper’s test. These work together to create an environment of trust and accountability, without bureaucracy. But it’s also uncomfortable. It requires tolerating people making decisions you’d make differently, resisting the reflex to add process when things go wrong, and letting people carry the weight of their own choices. Elizabeth describes the hardest part as “being comfortable in that discomfort.”

6. The keeper’s test is as much about recognizing great people as it is about removing the wrong ones. The test—“If this person told me they were leaving, would I fight to keep them?”—is often cited in its difficult form: the moment you realize someone isn’t the right fit. But Elizabeth uses it predominantly as an entry point for honest performance conversations that are deeply positive. Most of the time the answer is “I would fight so hard to keep you,” which creates the opening to articulate strengths, discuss impact, and name what’s working. Good feedback hygiene needs a forcing function; the keeper’s test provides one.

7. Specialization is trending down—adaptable generalists are trending up. We’re shifting away from narrow stack-layer specialists (pure frontend, pure backend) toward people who can navigate fluidly across layers. The same logic applies to business domain knowledge: the mindset of “I’m a payments expert, full stop” is less valuable than “I know payments well enough and I’m willing to imagine what the future version of this looks like.” The meta-skill is learning to learn, not locking into a single lane.

8. Netflix’s approach to AI fluency is a universal principle, not a level-specific expectation. Rather than rewriting career ladders to specify what AI competence looks like at each level, Netflix added a single aspiration across all roles and levels: AI fluency. What fluency means varies by function and seniority, but the non-negotiable minimum is the same everywhere—an open-minded, experimental mindset, genuine curiosity, and comfort with ambiguity.

[Matt Olson @ahbiscuits]

@cnakazawa Happy for you - and happy to see that Matts have a decent presence at Cloudflare 😀

[Satya Nadella @satyanadella]

https://t.co/vLmiBKTtX3

[Michael Grinich @grinich]

For the past several months, our engineering team has been building a new agentic coding system designed around a simple idea: the self-driving codebase.

These aren't just agents to write code on demand. They detect triggers, spin up secure sandboxes, gather dynamic context, open PRs, verify their work, unblock the next task, and learn from every failure.

We think the future of software engineering may look more like swarms of event-driven agents, running continuously, with humans setting direction and reviewing the work.

Ramp built Inspect. Stripe built Minions. Spotify built Honk.

We call ours Horizon. 🌅

Read more about what we learned and where it's going next:

[Matt Olson @ahbiscuits]

If you want a secure container for your coding agents, check it out - I use this daily and it allows me to run Claude, Codex, and others in yolo mode with no fear. https://t.co/pSuLFmzmpk

[Matt Olson @ahbiscuits]

Very cool that someone from the community chose to write a two-part blog series about my agent sandbox project - it's fun to share what I'm building and see so many others finding it useful! https://t.co/E4clfD3GNH

[Matt Olson @ahbiscuits]

Here's part 2, which really focuses in on agent-sandbox, the project I've been working on for the past few months: https://t.co/lpMEgXM9ec

[Michael Grinich @grinich]

The UI era is ending. 🪦

For 70 years we designed computer interfaces. Mainframe, CLI, GUI, Touch.

But with AI, the interface is disappearing. What will come next?

My talk from @mastra's conf this week:

[Sahil Bloom @SahilBloom]

An underrated red flag in a person is an addiction to being right. The most impressive people I know change their minds often in response to new information. It’s like a software update. The goal isn't to be right. It's to find the truth.

[Matt Olson @ahbiscuits]

It will be fascinating to discover how software engineering changes going forward.

I don't just mean the obvious things around speed, agent orchestration, or even agent/human interaction paradigms. I mean - will we uncover new ways of writing software that are more efficient and more elegant, but primarily because of the structure they give to agents and perhaps to enable agent coordination through higher parallelization - ways of working that are not necessary in the comparatively glacial pace we operate in today as humans, or are too complex for our feeble minds. New programming languages, new frameworks, new architectural models, co-discovered by humans and agents together, and then eventually by agents operating on their own with more autonomy.

For example, we came up with Object Oriented Programming because it was natural for humans to think in this way, but it doesn't necessarily mean it's the only or best way to do things, and it's usually far less efficient than other approaches. I suppose for now since LLM reasoning is based on human languages and the corpus of existing open source software, maybe we share similar ways of "thinking". It will be interesting to see how this evolves.

[Michael Grinich @grinich]

https://t.co/KrBfyVdFHZ

[Naval @naval]

If you do not direct your attention, it will be directed for you.

[Matt Olson @ahbiscuits]

Once Claude Code approval fatigue and ongoing permission management kicks in, the temptation is strong to run with `--dangerously-skip-permissions`. I think that's what we all want: run agents more autonomously, but in a locked-down sandbox where the blast radius of mistakes and/or prompt injection attacks is minimal/acceptable.

I have a workflow that works well for me, but want to expand on it. This weekend, I wrote up my approach and created a template for it. If you're running Claude Code or other agents locally on your Mac, check it out: https://t.co/kZPvw7i7hY

More to come: support for additional agents, network proxy for even tighter control and logging, etc.

[RŌNIN @ronin21btc]

I wasted my entire life because nobody told me this as a kid

[Matt Olson @ahbiscuits]

So far

[Prof. Lee Cronin @leecronin]

It is trivial to explain why a LLM can never ever be conscious or intelligent. Utterly trivial. It goes like this - LLMs have zero causal power. Zero agency. Zero internal monologue. Zero abstracting ability. Zero understanding of the world. They are tools for conscious beings.

[Notion @NotionHQ]

Now here’s a tough problem.
As a codebase grows, so does the rise of old code and outdated patterns. This leads to burdened engineers and large clean-up sprints.

So, we developed an open-sourced system to modernize the codebase without compromising developer speed.

But how? ⬇️

[Matt Olson @ahbiscuits]

@NeilMcDevitt_ @sama This is a more thoughtful, nuanced response

[Matt Olson @ahbiscuits]

ChatGPT has gone mad

[Sam Altman @sama]

!!