Some BIG news to share… I left venture capital to do the “0 to 1” thing. It was time to get in the arena. And I’m so proud to share that today, we got to 1. @askconciergeai is LIVE on Product Hunt 🚀
@rohanagrawal@cssetian
https://t.co/4SxVGpFXIP
Congratulations to the @Harvey team on releasing their Tenet model.
Human expert data is crucial for post-training work. We’re proud to have collaborated with @calvincongelado@vtrengarajan@ItsJulioPereyra@nikogrupen@gabepereyra, the Harvey research team, and hundreds of Mercor experts on this project.
@mhdempsey Reminds me of the story @taylormonks told me once about how he founded @BasicBlock_io - rode shotgun with truckers for months, just to watch and learn their workflows and bottlenecks.
+1 for "context engineering" over "prompt engineering".
People associate prompts with short task descriptions you'd give an LLM in your day-to-day use. When in every industrial-strength LLM app, context engineering is the delicate art and science of filling the context window with just the right information for the next step. Science because doing this right involves task descriptions and explanations, few shot examples, RAG, related (possibly multimodal) data, tools, state and history, compacting... Too little or of the wrong form and the LLM doesn't have the right context for optimal performance. Too much or too irrelevant and the LLM costs might go up and performance might come down. Doing this well is highly non-trivial. And art because of the guiding intuition around LLM psychology of people spirits.
On top of context engineering itself, an LLM app has to:
- break up problems just right into control flows
- pack the context windows just right
- dispatch calls to LLMs of the right kind and capability
- handle generation-verification UIUX flows
- a lot more - guardrails, security, evals, parallelism, prefetching, ...
So context engineering is just one small piece of an emerging thick layer of non-trivial software that coordinates individual LLM calls (and a lot more) into full LLM apps. The term "ChatGPT wrapper" is tired and really, really wrong.
Afternoon deep dives included:
⏩ All steak, no sizzle ways founders are leveraging AI with w/@ayush_concierge & @ijablokov
🌊 Creating cultures and teams built for change w/ Ted Souder & @andycloyd
💬 Breakouts for founder-to-founder pressure-testing and candor
Setting this up isn’t as easy at it should be. We solved that with https://t.co/ICpMpWj2gT - in <30 seconds you can connect your apps in 2 clicks, pick your favorite model (o3, Claude, deepseek, Gemini etc), and ask anything.
Claude + Zapier MCP just became the world's most diligent employee:
"Help me catch up on emails"
"Write a report on last month's P&L"
"Follow-up with Sam re: X"
"Status update on X project"
Works with any app that has a Zapier API (Gmail, Xero, Hubspot, etc).
SO USEFUL 🤯
The thing some people get wrong in thinking about AI is imagining the world as a zero sum system where we can only create a certain amount, and so AI creating means taking something away from people working.
This is entirely the wrong way to think about AI, and the economy generally. We should think about AI as a technology that democratizes access to some of the hardest and most complex things in the world so we can do way more. What happens as a result?
Think of all the filmmakers or writers without access to big budgets that want to produce new ideas. The scientists without extensive labs that want to do research. The marketers without 10 agencies supporting them that want to scale to more markets. The engineers without an entire team to build the next set of features or clean up their bugs.
The vast majority of potentially great work in the world is currently limited by the access to the capital or human resources that make all these things possible. And even when they do have access to those things, everything is just *slow*.
A breakthrough new drug costs billions and can be a decade of work. A blockbuster movie costs hundreds of millions and takes years to make. A marketing campaign takes millions and months to execute. And so on.
With AI, we start to unlock an ability to accelerate all of this work, and make it accessible to far more people, in a way that wasn’t comprehensible before.
And no, this doesn’t mean that everyone will start to do all of these things to point where there’s no value left. In every one of these fields there’s a very long tail of complex work and judgment requirement to produce real value. This gap will always separate consumers from producers. It just means that *more* people will be able to do these things when they’re motivated to do so.
In the process, many industries and even labor forces will expand as a result. Making a field easier doesn’t tell you anything about the ultimate curve of demand; all that matters is can that category offer more and more value for the world as it becomes more broadly available. For instance, we’ve seen a ~10X increase in the number of software engineers in the US from 1980 to 2020, and software is far more valuable today than it was then by at least 100X. Because the usefulness of software has gone up exponentially in that time period, partly as a result of how much easier we made it.
The same will be true for many other AI-enabled categories where there’s almost no shortage of demand potential, like healthcare, life sciences, coding, marketing, entertainment, education, manufacturing, logistics, legal work, and more.
AI will definitely change almost every sector as we know it, but not always in the ways some imagine.
AI has changed how we search and get stuff done, and now that extends to your work day.
We were already asking questions about our apps using Concierge’s AI enterprise search engine - we’re excited to add realtime, shareable knowledge cards you can trust. Great to partner with @rohanagrawal, @ayush_concierge, and Chris Setian and the @askconciergeai team. Check it out!
Enterprise Apps? ✅
Web Search? ✅
Trusted Knowledge Cards? Now here!
We’re excited to make @TakoViz's trusted knowledge search available to all Concierge users. Tako goes deeper than traditional web search by visualizing trusted vertical data directly in Concierge. On Concierge, you can now:
- Understand whether earnings surprised: “Nvidia earnings”
- Put the Wiz acquisition in context: “Google acquisitions”
- Review tomorrow’s matchup: “next Warriors game”
- Check the weather: “San Francisco weather”
- Get context about the news: “how much does Ukraine spend on its military”
And so much more. Check it out and let us know what you think!
Concierge is the first connected AI assistant that lets you talk to your SaaS apps in real-time ⚡️
It can read & write to your favorite tools like Gmail, Slack, Jira, Notion, Linear, Confluence, HubSpot, Attio, Salesforce, and Airtable. Ask Concierge anything and watch the magic ✨
Try it for free: https://t.co/UGu7uS3v0r