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Alertmouse is a lightweight brand monitoring tool that finds and tracks mentions across the web, including sources Google Alerts often misses. Users set up alerts in minutes, then receive filtered, prioritized results via email or API. It's built for marketers, founders, and creators who want signal without noise or enterprise bloat. Pricing is freemium, and your first alert is free forever. Paid plans are available for additional alerts and usage.
AI search is changing what gets surfaced and cited, making traditional SEO metrics like rankings and traffic less reliable indicators of performance. Growth Advisor Kevin Indig will join AirOps Head of Search Marketing Josh Spilker on August 13 to explain how to measure visibility through citations and share of voice. They'll also cover why methods like last click attribution and prompt tracking can mislead.
Katie Passarello, Co-Founder of PitchWell, explains how AI is changing public relations by making storytelling and media outreach more accessible. The discussion explores how businesses can improve visibility while maintaining the human experiences that make stories compelling. It also highlights why third-party credibility remains important as brands compete with the growing volume of AI-generated content.
Developers distrust campaigns but trust each other, so Cursor built its growth strategy around peer proof rather than paid promotion. It removed setup friction to create an immediate "wow" moment, shipped rough features in public instead of waiting for polish, and used a free tier to drive word of mouth while paid tiers converted engineers at companies like Shopify and OpenAI who started expensing it themselves. Cursor also turned community into its marketing department, paying 300 city-based ambassadors to run hackathons that double as tutorials, content, and recruiting all at once.
Fan Out Fox logs ChatGPT conversations and extracts key data.
A screenshot of how Nick Lafferty, Founding Marketing Engineer from Profound, commented about a product in a thread.
Marketing leadership is hard to hire and retain because the role is fragmented and founders still act as CMO.
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Fraud often starts with stolen data—not stolen money. That makes it harder to detect before the damage is done. This report by Javelin and Plaid [5] explores how fraud is evolving and the earlier signals that can help you catch it sooner. Read to learn: * Why new-account fraud, ATO, scams, and first-party fraud are
* How earlier, cross-lifecycle signals can help you detect fraud sooner. * What fraud really costs—from customer trust to operational strain.
AI shifts product management toward deciding what to build and how to sell it. Human judgment and customer insight remain essential.
AI generates more economic value while compute supply grows slowly, so the price of computing power could rise dramatically. This would favor frontier labs with the most efficient models, eliminate lower-value applications, and deepen the concentration of power in the AI industry.
Better models alone will not unlock physical AI. The strongest companies will build intelligent engineering systems that rapidly integrate, validate, deploy, and improve autonomous machines using real-world data.
AI can accelerate building. However, judgment, taste, and disciplined iteration are what make the result valuable.
Content creation can create influence, income, and opportunity, but it also brings pressure and criticism. Lasting success comes from authenticity, useful expertise, and prioritizing impact over attention.
As AI assistants become the front door to more tasks, users may interact with products without ever opening them directly. Designers must make products easy for agents to understand, invoke, and render while maintaining coherent native interfaces for deeper work.
Employees who see organizational contradictions must decide when to challenge them, translate them, conserve their energy, or walk away.
Behavioral health is booming, but complex insurance processes make getting paid difficult. Better billing technology can reduce administrative work and keep clinics financially sustainable.
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Seventy percent of IT leaders say agentic AI will improve productivity, but less than 25% reach production. Overcome the roadblocks with six steps to implementing search and AI. Grab the
The best tools cannot replace strong judgment and the ability to identify valuable problems.
AI can transform vague requirements into testable stories, handling the repetitive work while product managers retain judgment.
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Tines 3B [5] gives every team the power to build with AI, and gives IT the control to run and monitor that work safely. With Tines 3B: * Turn ideas into production-ready apps, agents, and automations in any stack. * Keep data secure at every step and ship workflows that improve over time. * Get end-to-end visibility on spend, workflow performance, and value.
On August 19th, hear from Headspace on how they're governing AI at scale with Tines 3B. Register now [7].
SpaceX has been hunting for a spectrum that works well in cities and dense areas for its wireless network. It is considering buying competitors to acquire the spectrum or competing at a government auction set for next year. The company has expressed interest in building its own terrestrial networks and has demonstrated a prototype mobile handset to some investors. Entering into the mobile market is capital intensive, so SpaceX could ultimately choose not to follow through on these plans.
OpenAI's annualized recurring revenue in July exceeded the company's entire second quarter. The growth was driven by the release of the company's GPT-5.6 series of models and ChatGPT Work, as well as growing adoption of Codex. OpenAI is under pressure to justify its $852 billion valuation as it prepares for its IPO. It has been racing to bring in new users to generate the revenue needed to help support its infrastructure spending plans.
DoorDash has received permission from the FAA to deliver packages by drone at altitudes below 400 feet. The drones will be built in the company's in-house robotics unit, DoorDash Labs. DoorDash Air aims to cater to any merchant, anywhere. The company will release more information later this year on its drones and how its drone program will fit into DoorDash's broader ecosystem.
China has accelerated its deployment of civilian and military hardware into orbit. The country's growing constellations of satellites could help it track events on Earth in real time and in greater detail than ever before. This has raised concerns among US officials, who see China's growing array of space-based capabilities as a quest to displace the US as the pre-eminent space power. Western analysts say that China is leading the world in research in sensors and satellite positioning technologies.
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Ever feel like you're shipping AI in slow-motion? This Datadog kit [12] includes an AI monitoring eBook, product briefs, and an on-demand webinar on software delivery best practices. Download it to get up to speed on delivering observable AI. Grab your Developer Toolkit for the
AI labs are moving faster than ever. However, capability is only half of the picture. Optimizing the cost per successful task makes models more affordable and less costly to serve. This article discusses techniques adopted in frontier labs to make API applications more efficient. It covers what happens when requests are sent to an AI agent, how the harness layer cuts repeated work, and more.
Prompts are dependencies. Changing them can shift downstream behavior with no warning, no failing build, and no obvious signal in the request pipeline. Treat prompts exactly like any other artifact that can change production behavior. Test them, give them a gate, and default that gate to blocking until proven otherwise.
Labs do not want to spend greater and greater shares of compute on inference. The point of inference revenue is to convince investors to spend more money to buy more compute to train bigger models. Spending too much on compute on inference signals that progress has stalled because it's not worth investing more in training. Labs believe that their models will continue to get better, so this only means that compute will get more expensive.
A new class of entrepreneurs is launching and running new million-dollar companies on their own. AI's ability to handle various administrative tasks makes it useful for launching solo businesses in many fields. The effect of one-person businesses on the labor market remains to be seen. While many people are worried AI will limit employment opportunities, these solo operators show how the technology can also open new doors.
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WhiteFiber validated 111.2 Tbps across 83km of dark fiber, within 8% of the physical speed of light. Two geographically separated sites.
The data center boom is pulling skilled trade workers into remote locations with some of the highest pay and bonuses the industry has ever seen.
numbat provides endpoint visibility into AI agent activity with local detection, optional pre-action blocking, and forensic reconstruction.
It may be awkward and weird and strange, but it's usually worth the shot to send a cold email.
There is a consistent pattern of OpenAI's alignment strategies working less well than Anthropic's.
Open-weight models are already being built into critical systems in the US.
Chinese founders face more pressure and liability, which results in more competent and ruthless companies, but also creates incentives for more froth and fraud.
Thinking Machines co-founder Lilian Weng left the startup after citing health effects from sustained stress and workload, then joined OpenAI. She said the pace required by the startup had become physically unsustainable.
Grok Voice Think Fast 2.0 is now available at $0.09 per audio minute. grok-voice-latest will switch over to the new model on August 5. The release makes Grok Voice more dependable in real customer workflows.
GPT-5.6 Sol scores just 7.8% on the ARC-AGI-3 benchmark despite having solved longstanding open problems in mathematics and beaten games like Pokémon FireRed. Benchmarks rarely measure AI models in isolation. They also measure less visible choices about API settings, harness design, and prompting. Researchers discovered that turning on retained reasoning and compaction in ChatGPT and Codex tripled scores and cut output tokens by 6x on the benchmark.
The team that built AlphaFold, which won Google DeepMind a Nobel Prize, has been taken apart. Most of the original AlphaFold-paper authors were reassigned over the past year. Nearly a quarter of them have left the company, with a few moving to Isomorphic Labs, an Alphabet drug-discovery spinout, and the stars going to Anthropic. The reorganization marks a turn away from the deep-science bets that made DeepMind's name toward the Gemini-powered AI scientist race.
1,224 employees from frontier labs, including many big names, recently signed an open letter that calls for the industry and regulators to prepare mechanisms for future coordination to control the pace of AI development. The letter indicates that many employees expect automated AI research to accelerate soon and are concerned about what might happen next and how fast things will go. Humanity is not yet prepared for this potential boom. The more work we do in advance, the better our options will become.
The GPT-5.6 model family was designed to balance capability and cost across a spectrum of tasks. OpenAI's research and technical teams made significant optimizations at every major layer of the stack to deliver these efficiencies. The improvements span across OpenAI's models, inference, and agent harness. This post looks at how OpenAI's team designed for efficiency through advancements in inference and its agentic harness.
logit_bias is an API setting that changes how likely a model is to select specific tokens. A researcher created a blacklist of words, converted the words into token IDs, and assigned those IDs a negative value to try to reduce the chances of a model using those words at an API level. This didn't work - it just made it harder for the model to select the next token, making resulting sentences sometimes look like they came from a less capable model.
This researcher trained their own LLM from scratch but discovered that their models were worse at instruction-following than the original OpenAI GPT-2 small weights, even when their model got better results in a more technical evaluation. This post is the first in a series where the researcher looks at the nature of the problem and explores options for what might be the cause.