Your buyers are using AI from first search to final decision. See what they're seeing with a free report from Evertune [8] - the marketing platform for brand discovery in AI search. Find visibility gaps, learn which sites get cited, and generate optimized content with
Google Ads can now automatically extract active promotions from landing pages and attach them to eligible Search and Performance Max ads. The account-level feature can surface offers such as “20% off” or “buy one get one free” without advertisers manually uploading each promotion. It applies only to eligible campaigns using location assets that do not already have manual promotions.
Google's Disavow tool is now mainly a recovery tool for sites hit with a manual action for unnatural links. Most sites don't need it after Penguin shifted spammy backlinks toward page-level devaluation. SEO efforts are better spent on useful content, UX, and earning credible links. Treat disavow as a targeted response to a confirmed manual action, not routine backlink cleanup.
Netflix uses geographic holdouts to measure channels that can't be A/B tested at the user level, including TV, OOH, and sponsorships. The approach measures incremental impact but requires careful decisions around test size, timing, media spillover, and carryover. Repeating tests builds stronger evidence, while campaigns without historical data require different methodologies. The challenge is getting leadership to protect test windows and accept the tradeoff between media delivery and measurement certainty.
Every AI workflow becomes a small maintenance job once it ships. Models change, connected tools get updated, and new edge cases surface. The person who built it is often the only one who knows how to fix it, so the workflow can quickly revert to manual when they're unavailable. Teams rarely plan for this upkeep, leaving it to compete with slower, harder-to-measure work like building visibility and trust.
You know the drill: ideas in Slack, context buried in docs, and Jira tickets you swear you saw somewhere. That was Maple too. See how they rolled out Jira Product Discovery to get ideas and prioritization into one place, plus the month-by-month playbook they used to go from one team's pilot to an org-wide standard.
AI makes execution cheaper and experimentation faster, but product expertise still matters. The advantage shifts toward judgment, customer understanding, taste, and verification.
AI agents have created "slop-creep" - the accumulation of unnecessary features, abstractions, and infrastructure built simply because they are cheap to produce. Without implementation friction, weak ideas survive longer, especially in large companies where software persists.
2026.09.08·
awaitinginput.substack.com·7 min read·TLDR Product
Pendo's Learning Lab [10] just launched with practical courses by product experts on building AI agents, sharpening product judgment, and becoming more AI-native. All courses are self-paced, free, and come with a badge worth sharing on LinkedIn. Explore the courses→
AI may create more analytics questions than it eliminates. The winning tools could look more like Excel than SaaS, giving agents a portable workspace to explore data and compound insights.
TLDR is hiring its first PM to help build the agent-first operating layer used across the company. We’re looking for a builder who has shipped real products / systems with LLMs. Click here to learn more [13].
AI can increasingly handle execution, but humans still choose the next hill to climb. Consumer AI's biggest opportunity may be helping people feel happier and more connected, not merely more productive.
AI creates little value when it simply speeds up a broken process. Companies should redesign the workflow first, then use software, agents, and humans where each is best suited.
Agents are smarter when they can search the web. But Google doesn't offer an API for web search results... so how are AI companies doing it?
Meet the worst-kept secret in the AI industry: the SerpApi web search API [4]:
👉 Scrape Google and other search engines (including AI overviews, Maps, Local, Shopping, and Knowledge Graph)
👉 Integrate with a dead-simple GET request that any agent can make.
👉 Used by NVIDIA, Adobe, Shopify, and even the United Nations.
Right now, TLDR readers GET 3 MONTHS AT 50% OFF, or start with 250
OpenAI believes that Artificial General Intelligence must be democratically governed for it to benefit all humanity. This can only happen through an informed public debate on the capabilities, risks, and safeguards of highly capable AI systems. The company has released details of its progress towards Recursive Self-Improvement (RSI) in recent months. It plans to continue to be transparent about its progress with RSI and believes that other companies should be required to publicly track their progress as well.
Tim Cook remains a powerful center of gravity at Apple. He will play an especially crucial role in certain areas, such as the company's dealings with the US and China, and its handling of the memory shortage. Cook will get a base salary of $2 million, twice the typical base salary of senior vice presidents and members of the C-suite. He will also receive cash bonuses and stock units that vest over time. The salary clearly shows that Cook's role will be very active.
Atoms, founded by Uber founder Travis Kalanick, is reportedly preparing for a hiring and acquisition spree. The company is also in discussions with Uber about how Uber can use Atoms' robotaxi technology. Uber has invested $100 million in Atoms. Kalanick has been cagey about his plans for the startup, but the recent moves could make it a major player in the autonomous vehicle industry.
A domain becomes playable when enough of its complexity can be compressed into a state where there is some reasonably stable repertoire of actions, interactions can be repeated, outcomes provide feedback about better and worse play, and the environment is stationary enough that lessons learned yesterday remain useful tomorrow. None of these conditions need to be perfect, as playability is a matter of degree. Far more of reality than we have previously expected can be turned into a game. Once something can be turned into a game, then it's possible to create a system that can beat it.
GLM-5.3 lifts Terminal-Bench 3.0 from GLM-5.2's 4.6% to 28.3%, and Flash is smaller and often enough. Both on Baseten Model APIs. Artificial Analysis and Baseten discuss benchmarking each against your tasks and serving them in production. Tuesday, 11 AM PT.
Security is always a productivity-risk tradeoff. Not giving access to agents can slow things down significantly. Frontier models are getting better and better at distinguishing real from malicious instructions in the content they read. We may end up trusting agents with access more than humans as models improve.
infra is an infrastructure-as-code tool that does what Terraform does. Users declare what resources they want, and infra looks at what their cloud accounts actually contain and reconciles the difference. This post details how its developer created the tool in two weekends in Lean 4, the problems it solves, and how the developer solved these problems.
TLDR is hiring its first PM to help build the agent-first operating layer used across the company. We're looking for a builder who has shipped real products/systems with LLMs. Click here to learn more [13].
OpenAI's president and co-founder, Greg Brockman, dropped out of college in 2010 to join Stripe. He eventually rose to become the company's CTO. He left in 2015 and co-founded OpenAI, where he served as CTO, and after a few years, he is now the company's president. This post features an interview with Brockman recorded before the announcement of Astra. It covers Brockman's background, the ChatGPT launch, OpenAI's place in the value chain, the company's commitment to alignment, the Hugging Face incident, and more.
AI models are now capable of taking a request from Slack and then building a feature from end-to-end, with humans just having to click 'merge' or 'deploy' at the end. There's not really much left for humans to do. Humans are still better at absorbing, parsing, and sharing context with each other. However, once that can be automated, the loop will finally be closed, and there will be nothing left to do but to pay the bill.
Apple publicly exposes the Apple Neural Engine through Core ML, while the compiler, program format, driver, firmware, and much of the machinery underneath it remains undocumented.
Demand for AI semiconductors is likely to surge with agent computer tool use, just as it did with the chatbot, reasoning, and agentic coding demand waves.
AI was supposed to be replacing workers. But has it?
Ramp's latest research [5] suggests something entirely different is happening (something almost nobody predicted).
As seen on Bloomberg, The Wall Street Journal, and The New York Times, Ramp's lead economist Ara Kharazian [6] takes you through the data this Friday, September 11th, for a special 30-minute briefing on what's really happening as AI is reshaping the workforce.
An OpenAI researcher says that reasoning models could continue advancing rapidly enough to contribute to their own development, creating increasingly serious alignment and cybersecurity risks.
Claude successfully created the first complete computer-verified proof of Fermat's Last Theorem in 11 days using Lean, automating the complex task initially proven manually by Andrew Wiles in 1995. The proof, verified via Prove2Me and Lean, involved 13 million lines of code and proved 29,500 intermediate theorems, proving AI's potential to ease the traditionally laborious formal verification of mathematical proofs.
Grok Imagine Video 1.5 agent delivers higher quality, better storytelling than previous releases. Powered by Grok's latest Image 2.0 model, it excels at connecting multiple shots together with greater continuity. The agent is now live on the web, iOS, and Android. A short video generated by the model is available in the thread.
Researchers gave GPT-6 Astra control of YAM arms under an Inspect Robots agent policy and gave it two tasks: it had to pick up a red block from a table and place it inside a bowl, and pick up a round blue puzzle piece by the knob at its center and place it into the matching circular groove in the board. Astra placed the block in 19 of 20 trials in the bowl task. It completed the puzzle insertion two times in 20. Astra completes the bowl task far more often than Fable at about half the cost per run.
Frontier labs may be applying probabilistic AI safety techniques to problems that require deterministic security controls. Recent agent sandbox escapes highlighted the gap between reducing harmful model behavior and reliably containing software.