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note · 2026-10-1246% of large companies have AI agents in production, and only 52% have defined when a person steps in
Schellman surveyed 525 US professionals who govern AI at companies with 500 or more employees. Agents reach production far more often where governance is mature, 78% against 22%. The escalation path is what lets an agent go live.
For IT directors and CTOs putting an AI agent into operationRead the note
note · 2026-10-12An AI coding editor raised lines added for two months, while code complexity rose 41.6% and stayed up
Carnegie Mellon researchers compared 806 open source projects that adopted a widely used AI coding editor with similar projects that did not. The speed gain faded after two months; static analysis warnings and complexity stayed up.
For CTOs and engineering leads of SaaS companies rolling out an AI coding toolRead the note
note · 2026-10-12A forward deployed engineer engagement that ends with a happy client and nothing changed in the product has failed
An essay by the person who led the program that trained about 250 forward deployed engineers. The job is to bring what the field teaches back into the platform, and one monthly question catches an engagement that did not.
For founders and CTOs of SaaS companies running forward deployed engineersRead the note
note · 2026-10-12Mid-market IT leaders say 25% of AI spend is lost to complexity, and only 15% have AI integrated in core operations
Freshworks surveyed 12,021 IT decision makers in six countries. 86% say AI complexity increased their team's workload and 36% remain stuck in pilots. The fix is an owner for the integration, not another tool.
For IT directors at mid-size companies deciding on the next AI toolRead the note
note · 2026-10-04Forward deployed engineers report spending 47% of the week with the customer and 31% writing code
The first survey of the role, 1,500 people at 154 companies, describes a job that is customer discovery with the right to ship code. Only 6% say they mostly build new product, and 71% travel at least monthly.
For founders and CTOs of SaaS companies hiring a forward deployed engineer or writing the job descriptionRead the note
note · 2026-10-04Three engineers, no one reads the code, and at least 1,000 dollars a day in tokens: the software factory that runs
One security company's own account of a software factory where code is neither written nor reviewed by humans. What replaced the reviewer was a set of scenarios the agents never see.
For founders and CTOs of SaaS companies deciding how much of their pipeline can run without a person reading the codeRead the note
note · 2026-10-0257.3% of companies have agents in production, and what stops the rest is whether the agent is right
1,340 answers to a survey published in June 2026. 57.3% have agents in production, one third name quality as the main barrier, 89% have observability, but only 52.4% run evaluations on a test set and 37.3% on live traffic.
For founders and CTOs of SaaS companies and IT directors putting an agent into an operation and deciding how to know it is rightRead the note
note · 2026-10-02Forward deployed engineer postings went from 200 to more than 5,200, and the skills list is the useful part of the count
US job postings with the title went from about 200 in 2024 to about 1,200 in 2025 and more than 5,200 in the first seven months of 2026. Three of the five most requested skills differ from a software engineer posting, with AI and workflow management in and agile methodology and software development out.
For founders and CTOs of SaaS companies and IT directors writing or reading a posting for the roleRead the note
note · 2026-09-30The success rate of an AI support agent is a number the seller defines
A vendor's own guide separates three numbers that get reported as one: conversations kept away from a person, conversations the AI kept, and problems actually solved. How each vendor defines resolved can move a reported rate by 20 to 30 percentage points.
For founders and CTOs of SaaS companies running or buying an AI agent for customer supportRead the note
note · 2026-09-16Teams write more code and ship less of it: main branch throughput fell 7% while feature branch activity rose 15%
CircleCI analyzed 28,738,317 workflow runs. Daily runs rose 59% year over year, the top 5% of teams nearly doubled theirs and the median team gained 4%. On the main branch, where code reaches production, the median team went backwards.
For founders and CTOs of SaaS companies whose agents write more code than the release process can absorbRead the note
note · 2026-09-15What a software factory actually ships: the pull requests its agents open merge one time in three on average
A software factory is a pipeline that takes specifications in and produces code out. LinearB's 2026 benchmarks measure what comes out the other end: pull requests opened by agents merge at 37% in fair organizations and 79% in elite ones, wait 4.6 times longer for review, and ship when a person owns them.
For founders and CTOs of SaaS companies building or buying a software factory, and the engineers who review what it producesRead the note
note · 2026-09-15AI written code duplicates more and refactors less, what 623 million code changes show
Four years of code changes, 2023 to 2026, and every maintainability signal moved the same direction as AI authorship climbed. Duplicated blocks up 81%, refactoring down to 3.8% of changed lines, changes to code older than a year down 74%. The fix that changed behavior in a client team was a tripwire.
For founders and CTOs of SaaS companies who let coding agents write code that shipsRead the note
note · 2026-09-15Code review of AI written code, review by exception instead of reading every line
When agents write most of the code, requiring a senior to read every change turns the seniors into the bottleneck. Rachel Laycock, CTO of Thoughtworks, argues for moving knowledge sharing, design and deterministic checks earlier, and reserving human review for a short written list of exceptions.
For CTOs and engineering leads of SaaS companies whose review queue grows faster than their outputRead the note
note · 2026-09-11The number to watch is code merged with no review at all
Two years of telemetry from 22,000 developers. Output is up, review time is up 441.5%, and pull requests merged with no review at all are up 31.3%. Review is where an AI initiative is won or lost.
For CTOs and engineering leads of SaaS companies whose review queue is growing faster than their outputRead the note
note · 2026-09-11Eight in ten people feel more productive with AI, 37% of companies see it in earnings
McKinsey's 2026 global survey of 1,719 respondents. Individual productivity gains are near universal, the effect on EBIT has not moved, and the 6% of high performers redesign workflows instead of inserting AI into existing ones.
For IT leaders and SaaS founders whose board expects AI results the P&L does not show yetRead the note