Fyxer buries $450 charges, Voss omits 55% vulns, Willison ducks dissent

Sources

How Fyxer built an AI executive assistant people trust openai.com

Fyxer uses OpenAI models, fine-tuning, memory, and real user feedback to organize inboxes and draft emails in each user’s voice.

Quoting Laurie Voss simonwillison.net

The cost of writing code collapsed, and the cost of reviewing, fixing and operating it is following, and I’m assuming it gets there. What’s left of making software is finding out what people actually want, defining it precisely, and making it pleasant to use. That cost is per piece of software and doesn’t transfer, so as the amount of software goes to infinity, which it will because there’s no ceiling on demand, that cost becomes the whole job. — Laurie Voss , We are all Product Engineers now T…

What blog posts influenced your thinking the most? simonwillison.net

My comment on What blog posts influenced your thinking the most? — Lobste.rs. An early Joel Spolsky one for me was The Law of Leaky Abstractions . I read that near the start of my career and it’s encouraged me to always be looking for improved understanding of the layers under where I’m working, just in case one of those abstractions leaks. A more recent one, from 2018, is Migrations: the sole scalable fix to tech debt by Will Larson. I absolutely love his idea that migrations (e.g. replacing o…

References

The SaaS News (Series B coverage) thesaasnews.com

Fyxer AI’s annual recurring revenue reportedly skyrocketed from $1 million to over $17 million in just eight months during 2025, with the Series B closing at $30M led by Madrona alongside Lakestar, 20VC and angels including Marc Benioff.

Growth Unhinged — ‘The AI-native growth team’ growthunhinged.com

An independent analysis of their growth team revealed they conducted over 514 experiments in a single year—roughly two per workday—using a lean team of four engineers leveraging Claude Code and Cursor.

Trustpilot reviews of fyxer.com trustpilot.com

Multiple users have reported surprise charges of several hundred dollars (e.g., $450 to €900) immediately following the 7-day trial period, and drafts introducing irregular 1.5 line spacing or stripping signatures and embedded images.

VerifyWise AI Trust Index — Fyxer verifywise.ai

Because Fyxer requires full read/write/send inbox access it belongs to the highest-risk tier of AI applications; reviews cite indefinite personal-data retention and terms that let Fyxer claim ownership over user ‘suggestions, ideas, and feedback.’

cmdk.email — Superhuman vs Shortwave cmdk.email

Superhuman reported that 60% of its ‘Auto Drafts’ are sent without any manual editing… Fyxer’s assistant-layer model aims to reduce the time spent touching the inbox, whereas Superhuman aims to make the time spent there as fast as humanly possible.

Madrona investment memo on Fyxer madrona.com

The founders required their original human EAs to record their screens and track their time meticulously, allowing the engineering team to ‘map the exact workflows’ of inbox management and meeting scheduling.

vipshek.com — ‘What is a Product Engineer?’ vipshek.com

Sherif Mansour of Atlassian credits Jean-Michel Lemieux (former CTO of Shopify) with using the term to describe developers who engage with the ‘why’ of a feature rather than just the ‘how’… By the early 2020s, what was once a startup oddity began appearing in major job listings as a distinct career track.

jonas.rs summary of GitClear 2025 code-quality report jonas.rs

The frequency of code duplication increased eightfold in 2024, while ‘moved lines’—a key indicator of refactoring and code reuse—dropped by 70% compared to 2022.

Interclypse — ‘The AI Trust Gap’ interclypse.com

72% of developers use AI tools daily, [but] a staggering 96% do not fully trust the output to be functionally correct.

Medium summary of Stanford AI Index 2026 medium.com

Employment for software developers aged 22 to 25 has plummeted nearly 20% since 2024, marking over 33 consecutive months of decline.

CIO.com — ‘How agentic AI will reshape engineering workflows in 2026’ cio.com

Engineers use AI in roughly 60% of their work, [but] only ‘fully delegate’ 20%, shifting their primary value to ‘orchestrating long-running systems of agents’ rather than line-by-line creation.

Recorded Future / Veracode 2026 findings recordedfuture.com

Roughly 55% of AI-generated code contains at least one security vulnerability, often in areas like cross-site scripting (XSS) or log injection… these flaws scale at the speed of the AI, potentially overwhelming manual security review cycles.

Wikipedia — Leaky abstraction en.wikipedia.org

Critics from the functional programming community argue Spolsky’s law is a triviality resulting from weak type systems; abstractions grounded in mathematics (bignum classes, verified monads, sets, integers) behave identically regardless of implementation and do not leak.

Hacker News discussion (item 46092217) news.ycombinator.com

Larson’s techniques can lead to ‘engineering ivory towers’ where infrastructure teams force complex changes on product teams, causing friction with the business and potentially leading to organizational gutting during layoffs.

Medium — ‘The Engineer/Manager Pendulum is Dead, Long Live the Pendulum’ medium.com

In an efficiency-focused market with lower job security, swinging back to an IC role can be perceived as a demotion by external recruiters; if a manager stays away from hands-on work for more than 2–3 years, returning to a senior IC role becomes impossible without a downgrade in seniority and pay.

John Barton — ‘Pendulum on the Ladder’ johnbarton.co

The pendulum is merely a way to survive a flawed status quo rather than fixing the underlying organizational designs that force the choice in the first place.

daily.dev — Best of Lobste.rs digest daily.dev

Recurring 2026 recommendations pair Spolsky and Larson with Alexis King’s ‘Parse, Don’t Validate,’ Rich Hickey’s ‘Simple Made Easy,’ and Sandi Metz’s ‘The Wrong Abstraction’ — with Sean Goedecke’s ‘In defense of not understanding your codebase’ sparking debate that maintaining a full Naur theory of a system has become impossible.

arXiv 2606.05608 — empirical study of AI-authored commits arxiv.org

A 2026 analysis of over 300,000 AI-authored commits found that 15% introduced code smells or security issues that persisted in repositories long after deployment, reviving Brooks’s distinction between accidental and essential complexity as the ‘Mythical Agent-Month.’