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Replace rigid activity benchmarks (emails sent, calls made) with quality-based outbound metrics that measure personalized outreach, events, social connections, and solutions-based engagement. Learn from top reps and rebuild the outbound playbook.
Build a basic ICP score using Clay to identify target accounts and create a targeted list for outreach. Build a Clay table to set up basic intent signals (e.g., prospect visited your website, hired someone with a relevant title) and fire alerts into Slack for real-time notifications. Build a Slack canvas to create an ongoing briefing of focus areas from the signaling system.
Shaun Crimmins recommends using a forward deployed engineer to win over technical stakeholders, because engineers respect other engineers. Use forward deployed engineers (FDEs) to build technical champions by embedding them with the customer to build and ship solutions that improve the customer's daily workflow. Arm the forward deployed engineer with context about what the customer is trying to accomplish and what matters to them before the engagement. Have the FDE ask the customer engineer about their daily workflow, challenges, and world to uncover pain points before building a solution. Have the FDE return to the customer engineer within a week with a built solution that addresses the uncovered workflow challenges.
Shaun Crimmins recommends aligning on success criteria up front before starting a pilot.
Shaun Crimmins recommends mapping each value touch throughout the pilot in advance, planning exactly when you deliver value and what your ask will be. In week one, improve a metric the customer didn't know they had (e.g., knowledge base coverage from 30% to 90%) and hand them the improved asset at the end of the pilot regardless of outcome. Use the improved metric from week one as leverage to ask for access to additional tools or integrations in week two.
Shaun Crimmins recommends including three slides before dropping into a demo: the biggest problems learned in discovery, how you solve those problems, and what success looks like today. Set up your demo so it could work without you in the room.
Before launching an AI agent, ensure it works exceptionally well, not just 'good enough', to avoid high churn. Many AI agents are average or require babysitting and manual work, leading to high churn rates of 20-40% per month. If you overpromise on an AI agent's capabilities, customers will cancel within a month or two. Do not build an AI agent that is solidly mediocre or only does 80-90% of the job; it's not enough to replace a human. Tune and optimize the AI to be exceptional. Do not ignore the cost of the AI agent; it could hit your profit.
Rob Walling provides techniques to overcome fear of social interaction: hire a therapist or coach to join calls initially, use an LLM to draft outreach emails and prepare call scripts, practice sales conversations out loud (record yourself, use a mirror, practice while driving), and take small progressive steps. He emphasizes that repeated practice trains the nervous system not to go into fight/flight/freeze mode, and reminds that social interaction is not a life-or-death threat.
Derrick Reimer recommends using an LLM (e.g., Claude Code) to help a new developer understand the codebase by asking questions about major subsystems and reading Git history. He also suggests pair programming for 1-2 hours a day for the first couple of weeks to infuse team ethos and build rapport.
confident
Erik Allebest advises not assuming a growth spike from a macro event (like COVID or The Queen's Gambit) is permanent; wait to see if the baseline holds. He describes the 'white-knuckle' scalability issues across product and tech during rapid growth, and notes that growth became more predictable after building the right team.
Hodak recommends pairing a long-term research project (e.g., bio-hybrid neural interfaces) with a near-term commercial product (e.g., retinal prosthesis) to sustain the business, and emphasizes that having a real business is critical for a moonshot.
Choose exercises where the arm finishes back behind the body, putting the long head in its most shortened position.
Choose exercises that put the shoulder in flexion and the elbow up overhead to stretch the long head of the triceps.
Vlad Tenev describes the Trump accounts program, which gives every child born in January 2025 onward (for the next three years) $1,000 seeded by Treasury, with the idea that every child from birth can own a chunk of the US economy through a low-cost diversified S&P 500 ETF. Robinhood was selected as the sole initial trustee and broker for the program, working with BNY (America's oldest and most storied bank), Treasury, and the IRS. Robinhood is powering the infrastructure and building the app, which they see as their way of serving their country.
When a workflow element does tool calls, Ramakrishnan Lokanathan says the eval objective should be: what is your tool call ability and the tool call accuracy at that point. The eval has to be designed for tool calling and not for a different process separately.
The creator advises incorporating touching into the date and having moments where you look deep into each other's eyes, presenting these as key elements that build attraction and intimacy.
Zach Lloyd argues that storing all agent traces and artifacts — recording everything the team's coding agents do — is what makes coding agent activity the raw material for improving the factory; without it, you lose the raw material needed to improve over time.
Supabase is announcing Supabase Compute, a long-running serverless compute offering that runs in the same private network as the user's database for co-location and low latency, is a full compute instance, can run agents, supports long-running workloads like chunking and embedding, and allows direct Postgres connections from compute.
Kevin Hou announces that the agent manager is now a standalone app decoupled from the IDE in Antigravity 2.0, and describes its core purpose of managing many agents in parallel with the human in the driver's seat.
To leverage new models same-day, Optiver benchmarks them on golden sets (requiring a mature evaluation framework), partnering with key customer trading teams to collect and onboard their benchmarks so new models can be run immediately and results shared company-wide. A new model must be made available in the gateway with the right APIs, interfaces, and cost management; harnesses often need updating, which Optiver manages and delivers; and after benchmarking they keep the communication line open — what they looked into, how well it works, how to use it, and their recommendation.
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