Spike

Open your inbox and the most important thing is already waiting for you, summed up before you've read a single email. The iGPT Brief Agent is open source. It reads your inbox and hands you a clean brief: what's urgent, what's waiting on you, what's due, and what to do next. Like having a chief of staff triage everything before you start your day. The hard parts of connecting to email and making sense of it are already done, so you can build your own agent on the same foundation. Connect your inbox and see what matters most right now. https://lnkd.in/dPRz9WGq

If you can write a prompt, you can build an end-to-end invoice tracker from your inbox. All you need is an hour or so and the iGPT API. It does the work that used to take months of engineering. It indexes every email and attachment in the inbox, reconstructs threads, resolves the same vendor across four sender addresses, determines whether it is a charge, renewal, or refund, and returns everything as schema-validated JSON. What's left for you is the prompt and the routing. Tell iGPT what to extract, hand the output to Slack or a sheet or whatever the team already uses, ship. Invoice tracking is just one example. The same pattern works for hiring pipelines from recruiter threads, contract tracking from legal email, customer health signals from support inboxes. Anywhere structured answers live inside unstructured email. The tools your team pays for every year are an afternoon's work when the hard part is already an API call away.

You can build your own invoice tracker this afternoon. One prompt to iGPT pulls every invoice, receipt, renewal, and refund from your inbox, ready to be routed to Slack, Sheets, or QuickBooks. Instantly detect: - Duplicate billing - Overspending on team seats - Upcoming renewals on unused tools Get the same accuracy as a five-figure subscription, the same coverage as a quarter of engineering, with none of the cost or time. If you can write a prompt, you can build this. Walkthrough in the post below. https://lnkd.in/dVbfECNJ

Want to know why your AI hallucinates even when you give it the context? It's probably using RAG. RAG chops content into chunks and pulls the ones that look most similar to your question. That works for documents, but email isn't a document. Email keeps copying itself into every reply and buries the current state under quoted history. So the model sees real text and reaches the wrong conclusion. iGPT reconstructs the thread first and returns what actually happened, with citations back to the source. Full breakdown: https://lnkd.in/dZ2zkYtf

"Where was this discussed?" If your team asks that question more than daily then you're not short on tools, you have too many. New on the blog 👇 https://lnkd.in/dzM-Nn6G