.@krakenfx is hiring a Staff Product Designer for AI Products. Remote US, $127K to $254K base. You'd be the designer on a personal finance agent, zero to one. A few notes on why I think this is a good one.
Fun conversation with @DWeisburd on How I Invest.
One idea that stuck with me: venture is the only asset class where you have to sell your money to the company.
Everything else about VC follows from that.
A user sent us their PDF
HomeFig agent built it in 7 mins using real SKUs
So
- fully accurate construction plans
- real Bill of Materials with products you can buy
Seeing this for 1st time was a visceral experience for me
Our goal is for our users to 5x their sales
Your AI is vaporware without deep integrations with your customers’ systems of record.
Introducing @WithAmpersand: integration infrastructure for enterprise agents.
We power 11x, Orb, and Square's ability to take agentic action in systems of record like Salesforce, SAP, NetSuite, and Workday.
Ask anyone serious about building AI and they’ll tell you:
- The SaaSpocalypse didn’t happen. The world depends on CRMs, ERPs, HRISs, and ITSMs.
- Your customers customized their deployments beyond recognition.
- Systems of record companies are basically monopolies. They never had to make their APIs and MCPs user-friendly.
- Docs don't explain half the weird edge cases you'll hit.
- One bad write can blow up your pilot or renewal.
- Once you finally get it working, someone changes a field and it breaks again.
The world's data lives in structured databases. AI needs a translation layer to work with it.
So, for your AI to truly transform the way enterprises work, you'll need deep integrations built for:
- scoped permissions
- bi-directional actions
- real-time speed for agents
- custom objects, fields, and workflows for each of your customers
We built Ampersand to power the future of software.
AI didn't trivialize writing integrations. It made them the critical path.
I believe that deeply, so I didn't make a launch video about Ampersand.
Instead, it's the best builders I know explaining just how big of a challenge this is.
Introducing Mo, the world's first AI QA engineer
Point it at your app and 100+ agents bug bash it in parallel. Every bug comes back with repro steps, logs, and a video
In our evals vs Codex with Playwright MCP: → 3.8x more bugs → 9x more bugs per hour → half the cost per bug
RT + reply "Mo" for $250 in free credits. Drop your app URL, Mo will bug bash it and DM you the report today
Today we are launching the @AugmentMarkets Private Liquidity Network, a standing self-serve trading venue for units of pre-IPO SPVs. Details in the thread:
agenthook gives coding agents a webhook-backed inbox.
When a deploy, CI job, or another agent/service finishes after an agent’s turn ends, it can notify the agent instead of making the agent block and monitor.
introducing
═══════════ 𝚌𝚏𝚘.𝚊𝚒 ═════════════
tl;dr
1/ runway is now https://t.co/Uqg6xlaJIU
2/ you can hire @arithecfo and he can start TODAY
3/ you can give @arithecfo a test drive by replying to this thread with any ridiculous thing you want him to model for you, and he'll come back to you with a beautiful, detailed, fully wired financial model
... in 30 minutes or less
now, story time:
🧵 1/n
BREAKING: Sacra’s (@sacrainc) private markets data is now live in Artemis’ AI Analyst.
We’ve partnered with Sacra to bring a deep private-company data directly into Artemis, including:
• Revenue and operating data
• Valuation and funding history
• Company and firmographic data
• News and market updates
• Expert interviews
• Analyst memos
Private markets research, made easy with Sacra + Artemis.
We were really impressed with how fast OAI's new gpt-realtime-2.1 was while still being able to call tools, so we wired it into our OS agent running on my phone. Now I can completely control any app on my phone while I'm biking to work
Today we're launching a whole new Arrows.
Every deal gets a gameplan.
Arrows gets it done.
Why? Because your best reps have a gameplan for their best deals... but it's all in their heads and is executed inconsistently.
Until now.