Article · 2026-08-12 · 6 moments

Stop being skeptical about AI for development with Charity Majors

In 2025, it was rational to be skeptical about AI. In 2026, it's not, anymore. With Charity Majors, CTO and co-founder of Honeycomb. ✦ AI generated

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GUEST Charity Majors HOST Gergely Orosz

timeline · colored by role

Prediction◆

AI became a generational change in November 2025, primarily because coding harnesses such as Claude Code turned from shell scripts into serious infrastructure.

Charity Majors identifies November 2025 as the point when her view of AI shifted from skepticism about its generational impact to seeing it as transformative. She credits the coding harness, especially Claude Code, more than the underlying model alone.

transcript

Charity Majors: Charity’s turning point in seeing AI as a generational change was in November 2025. This was due to Opus 4.5, but Charity argues that the coding harness (Claude Code) made the bigger difference. Because thanks to Claude Code, harnesses went from being more of a shell script to serious infrastructure.

Mechanism◆

AI may shift software development from treating code like pets to treating it like cattle, because generating and replacing code can become cheaper than editing it.

Previously, writing software from scratch was much more expensive than modifying existing code. AI makes it feasible to generate many alternatives quickly, potentially enabling teams to replace faulty code rather than repair it, analogous to modern infrastructure practices.

transcript

Charity Majors: AI could have the software industry go through the “pets” to “cattle” change that compute infra went through in the 2010s. Up to now, writing software from scratch was far more expensive than editing existing software. But now, generating hundreds of variants of a function can be done faster than how long it would take you to hand-write it once. Charity believes that we might be at the beginning of the transition from “pets” to “cattle” that happened at the hardware infrastructure layer. Before the 2010s, configuring and repairing individual servers was commonly done. But with tools like Terraform and Kubernetes, individual servers having issues are no longer fixed up: they are re-created instead. Charity thinks the same might happen with code, sooner rather than later. When there’s an issue with the code, generate new code that solves it, and is verifyably correct.

explains mechanism · 1

Claim

Code review is overrated and is among the least valuable things humans contribute to software engineering.

Charity argues that humans are better suited to discussing problems and deciding what to build than manually checking code for correctness, syntax, and bugs.

transcript

Charity Majors: Her contrarian take: code review is overrated, and the least valuable part of what humans add to software engineering. Charity says that humans are good at conversations and deciding what to build, not reading code to check for correctness, syntax and bugs.

supports · 1

Mechanism◆

AI-generated, non-deterministic systems require more engineering discipline, especially stronger testing, evaluations, and conformance validation.

Because engineers trust AI-written code less when they did not write it themselves, confidence must be rebuilt elsewhere in the process. Charity locates that trust in validation mechanisms such as tests, evals, and conformance testing.

transcript

Charity Majors: Non-deterministic systems require more engineering discipline versus before. With code written by AI, we’re reducing the trust in the code (because we no longer wrote it), so we need to increase trust at the other part of the development process. Specifically, at validation: with things like tests, evals, and conformance testing.

explains mechanism · 1

Claim◆

Both AI enthusiasts and skeptics should tell the complete story by acknowledging AI’s benefits as well as its costs.

Charity says AI is producing genuine gains, including rewrites and the removal of toil, but argues that many people celebrate those gains without recognizing the costs imposed on colleagues. She urges both camps to describe the entire picture because everyone is experiencing the transition together.

transcript

Charity Majors: “There are some really incredible things happening in software right now, for example, with rewrites and with automating away toil. Not a single person that I’ve talked to would give up using AI. But half of the people are seeing the wins, and they’re not connecting it to the cost, which makes them think that their coworkers are just afraid of getting automated out of existence. So that’s my beg to everyone who listens to this: tell the whole story! Talk about the costs as well. We’re all in it together.”

Prediction

Engineering leaders should move toward AI immediately, and anxious directors should consider returning to individual-contributor work because it offers more agency.

Charity’s advice is to run toward technological change rather than wait for it, putting AI experience on one’s résumé now. She also says that directors facing anxiety may regain agency by returning to IC work, though the opportunity to do so may narrow.

transcript

Charity Majors: Charity’s career advice for engineering directors: run towards the waves, and get AI on your resume, immediately. It’s an anxious time to work in tech, thanks to all the change, driven by AI. Charity reminds us that anxiety and excitement are physiologically almost the same, but the difference is agency. When you have no agency, you’re more likely to get anxious, and when you do, you’re more likely to get excited. So her advice to anxious engineering directors: consider going back to IC work, where you’ll have far more agency. IC work is well-respected, getting back to it has never been easier, but the window to do so is closing. As she put it: “The next time you’ll have a job interview, you’ll be filtered out if you don’t have AI experience.”

supports · 2

Highlight slides

AI’s Generational Turning Point✦ from: AI became a generational change in November 2025, primarily because coding harnesses such as Claude Code turned from shell scripts into serious infrastructure.Why Coding Harnesses Mattered✦ from: AI became a generational change in November 2025, primarily because coding harnesses such as Claude Code turned from shell scripts into serious infrastructure.AI may turn software from pets into cattle✦ from: AI may shift software development from treating code like pets to treating it like cattle, because generating and replacing code can become cheaper than editing it.From repairing servers to recreating code✦ from: AI may shift software development from treating code like pets to treating it like cattle, because generating and replacing code can become cheaper than editing it.AI-Generated Systems Demand More Engineering Discipline✦ from: AI-generated, non-deterministic systems require more engineering discipline, especially stronger testing, evaluations, and conformance validation.Validation Becomes the New Trust Layer✦ from: AI-generated, non-deterministic systems require more engineering discipline, especially stronger testing, evaluations, and conformance validation.Tell the Whole AI Story✦ from: Both AI enthusiasts and skeptics should tell the complete story by acknowledging AI’s benefits as well as its costs.Benefits Can Hide Costs✦ from: Both AI enthusiasts and skeptics should tell the complete story by acknowledging AI’s benefits as well as its costs.

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