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To drive AI adoption across 32,000 engineers, Cisco guaranteed employees that if they don't use AI they will lose their job (the inverse of the usual fear), told non-adopters Cisco is the wrong place while offering full tooling and support, and gave everyone unlimited tokens to start.
All internal apps are automatically protected by Okta SSO so only employees can log in, requests are logged and auditable, secrets live in Doppler rather than code, and sensitive apps with PII or customer data cannot be accessed outside the company.
Matt Gibiec argues that letting agents do everything without human oversight would create a messy environment and that pushing fixes to production without human approval means losing control. He recommends maintaining human-in-the-loop control over agent actions and giving the human the final decision on whether to push a fix or feature to production, reviewing the full SDLC context before deciding.
Abhi Arya's principle: to avoid auto mode, you don't hand your agent an API — you hand it tools that carry the overall expertise, such as the right patterns, the state, and the validators. Instead of one create step to call over and over and praying the agent assembled it right, he built tools that understood how their internal dashboard or product works.
Dr. Elissa Epel advises: when you know the effort is productive, work (muscle it); when you know there's a brick wall, let go (release it). Letting go is a wise, discerning way to mitigate stress in the right situations and at the right time. You can't muscle through everything. Huberman adds that dropping the rope (letting go of a struggle) frees up energetic resources that were being consumed by a high-demand, conclusionless effort.
There is a huge difference between getting the whole job done versus getting everything except for the last mile — the last mile can feel worse than a non-starter. If a tool is a non-starter, the user can just do it themselves or try another route, but if it gets 99% there and then fails, it's a worse unfulfilled promise. Computer use will always work — it might be slow or cost a lot of tokens, but it will get the job done all the way.
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Tara Sesha says she shifted her mindset from getting it perfect a priori to shipping something and iterating as quickly and effectively as possible, because nothing compares to actual empirical evidence of seeing users try and use a product before theorizing; urgency matters more than polish when shipping AI-era products.
Knowing if your agents are executing well comes down to measuring the right things: measure outcomes, not tokens. Lines of code and tokens generated are gameable metrics not associated with outcomes. Token usage is Goodhart's law in real time — engineers optimize for it and it stops being a good metric. Token leaderboards at big companies just encourage profligate spending. It's not about who spends the most on tokens; it's about who gets the highest leverage outcomes from that spend. Don't token max — measure what actually matters.
After selecting matching layers, hit paste to paste an image into all matching frames at once; pasting after a single command-click only pastes into one frame, not all matching frames.
Click an object's position property in motion mode to create a keyframe at its current state; move the landing keyframe to around 0.4 seconds on the timeline; with the playhead at the first keyframe, drag the object to its starting position to define where the animation begins.
Animate shadows by scaling them up and fading them in as objects land: create a keyframe on the scale property, un-constrain scale so width can be animated independently, animate shadow scale from about 20% to 100%, and set the first keyframe's opacity to 0 and the last to 100 so the shadow fades in.
Copy keyframes from one animated object and paste them onto other objects to give them the same animation, then stagger the animations on the timeline so objects don't all come in at the same time.
To create a relationship between an object and a frame, go to prototype, drag the connection, choose smart animate, and set a nice easing curve; set the interaction to on-click navigate to the target page (pizza 2).
Multi-edit in Figma selects matching layers across multiple frames; command-click on a gray square inside a component and return to design mode to access it.
Motion is created by stamping a keyframe at the starting position, moving the playhead to the target time, and stamping another keyframe at the new position; a position widget appears over a selected rectangle on the canvas allowing its position to be changed while scrubbing the timeline.
Use the after delay trigger to automatically navigate to the next frame after the intro animation finishes; set the interaction animation to Smart Animate for the frame-to-frame transition.
Lore says you need to take risks and be comfortable with an 80% chance of failure, be willing to put in as much time as necessary, and that incredible work ethic combined with risk-taking is the best starting point. Being able to take risk while being comfortable failing takes things to the next level.
Lore's team took a page from the Walmart and Target playbook: if the loss leader works in stores, they could afford to lose even more money online because they had far more products to sell. They stuck to the thesis that they would eventually buy diapers direct and profit from other goods.
Lore explains that diapers were a loss leader for Walmart and Target, driving parents into stores to buy everything else. Online it was an even bigger loss leader because bulky diapers are expensive to ship, which is why no one had sold diapers online before.
Dr. Morin warns that doing several top-speed sprinting sessions per week for prevention can overexpose players who run with problematic patterns, effectively shooting them in the foot by doing too much on an unprepared body. Instead, rule number one is to work first on the running pattern so that the players are ready for the coming sprint overload. He invokes Stu McMillan's principle 'form first, load second' — you would never send athletes to weightlifting without educating them to lift correctly, and the same applies to sprinting.
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