The combination of real-time data and AI is going to be extremely powerful.

Scoutpost now has a ChatGPT plugin and a Chrome browser extension! You can schedule web monitors directly from the page you're working on, or install the GPT plugin to run the entire application in your chat. You can connect any agent to Scoutpost and ask it to set up scouts on web pages, social accounts, aircraft and vessels, city councils, or a beat and your monitors will run on a schedule. When something changes or matches what you asked for, you'll get alerted by email and a dated, source-linked record of what was found. It's now out of public beta and available through @MuckRock or the Indicator Lab. The code is open-source. scoutpost.ai/

On October 28th @CraigSilverman and I will be giving a free workshop about using AI agents to assist with OSINT and digital investigations. We'll be sharing examples from our latest work, talk about how to get set up (with a blend of paid or open-source options) and take questions. You can sign up here: indicator.media/p/free-webin… Hope to see you there!

I'm opening OSINT Live on October 15 to talk about the shift I see coming in investigative work, from clicking alone to calling the shots. Sherlock is the archetypal investigator persona, he works the whole case out alone (sorry Watson) and things move as fast as he does. Now let's imagine a modern-day Sherlock running his practice like Danny Ocean. He delegates the searching and cross-checking to a crew of specialized agents working together while he works multiple cases. How much more could he take on? And how much faster could he solve each crime? I think this is how more OSINT work will get done. Complex research opens up too, because technical ability stops being the barrier to digital digging. During the session I'll walk everyone through how to build agent crews and custom investigative workflows. You can register here: skopenow.com/osint-live

Last week we had the first Indicator Lab Session. As a part of the pilot the slides are publicly accessible if you want to see what was covered. Future sessions might be: • newsroom operating tours to hear teams unpack real workflows or automations used to accelerate their work • investigation debriefs to look at case studies of reporters and researchers using AI in investigations • hands-on sessions with practical demos of how I used AI on a reporting project • deep-dives to zoom in on a specific subject or paper, like last week I focused the session on understanding harnesses: what they are, and how newsrooms and investigators can build their own repeatable workflows on local models with harness engineering. I think this will become commonplace as token costs explode and adoption increases, especially when proprietary or sensitive data is involved. Spotlight is a blueprint for this - I engineered a harness around the investigative workflow, tuning a small model to comply with the requirements so it runs predictably at scale. The architecture also includes a smaller Recursive Language Model to absorb long, noisy source material and offload that from the orchestrator. Next month is likely to be a newsroom operating tour! lab.buriedsignals.com/sessio…

Spotlight — the agentic OSINT pipeline — can now run locally on your machine! I shipped it with local models from day one but it was unstable — the models were either too big for my Macbook or too small and drowning mid-investigation. So I began a long and arduous quest... To make Spotlight run end-to-end on Gemma4 12B (a 7 GB download, 32GB RAM will hold it comfortably). It took weeks of relentless keyboard bashing and a ridiculous amount of tokens, but it works. The entire pipeline — orchestrator, review gates, scraping, browser automation, adversarial review — runs locally on a small model. Which means that performance on larger local models is also dramatically improved. Quest completed! The recipe and learnings are open below. Newsrooms and investigators can reference this as a method to run their own workflows on small tuned models with no per-token bills and full data ownership. Particularly useful if you want to run a sandboxed investigation on sensitive or dangerous data. spotlight.buriedsignals.com/…

Big Spotlight update. The headlines: epistemic grounding, sensitive mode and a Qwen 3.6 27B fine-tune. Borrowed from Stanford Plato's work on metaphysical grounding: a source is not the same thing as a claim it actually supports. The system now records why evidence justifies a claim, and flags adjacent evidence, repeated-but-not-independent sources, and confident synthesis from material that does not prove the point. Sensitive material now goes into a separate vault instead of the default knowledge base. Cloud agent sessions keep querying the regular index; local-model sessions can opt into the sensitive one when the work should stay on-machine. The new Qwen 3.6 fine-tune requires heavy machinery but it benchmarks much better than the base uncensored model on investigative prompts. Thanking the community for flagging unsafe shell-command patterns and catching the Ollama `/no_think` empty-response bug, this release is sharper because of that feedback. Spotlight can accelerate the reporting trail, but it doesn't replace human judgement or accountability. This release makes that explicit: the final report is intended as a starting point for humans to keep digging. You can try it here: spotlight.buriedsignals.com/