Open source models will cover general everyday AI tasks, while frontier proprietary models continue to push capabilities for specialized and complex w...Show more

Local inference on models like Llama 3.2 is now feasible, enabling on-device LLM use with internet search augmentation and reducing dependence on clou...Show more

Prioritize LLM evaluation based on real-world task completion and cost efficiency rather than solely on benchmark scores.

Generic agent frameworks aren’t sufficient; AI copilots must be tailored like a glove to a domain expert’s dynamic, branching workflow to truly accele...Show more

Using a tailored agent UI for web research can be more efficient than ChatGPT, as it automates multi-step breakdowns and progress tracking in one shot...Show more

Open-source agent systems like Deep Agents and custom CLIs don’t always run continuously, so developers should anticipate intermittent failures and op...Show more

Keeping track of actions via simple note-taking skills can significantly improve agent performance and transparency.

Running tools constantly in the background can be distracting or unwanted, so developers may prefer on-demand execution.

Breaking complex prompts into simpler sub-agents is more delightful and efficient than endless iterative prompting to maintain context.

Cameron Rohn argues that AI agents must be managed similarly to human employees, requiring clear instructions and ongoing guidance to deliver desired ...Show more

Without injecting fresh context between chained AI agent processes, iterative processing leads to diminishing returns and deteriorating outputs.

AI-driven generation of product frameworks can outperform manual hacking of generic SaaS tools by delivering exactly the product philosophy you need i...Show more

There’s a missing category of AI tools between design environments like Figma and planning tools where you translate designs directly into a roadmap f...Show more

Tom quips that niche devices like an Apple Vision Pro or DGX arc often end up as expensive paperweights if not fully leveraged.

High product velocity in AI startups is critical as the industry is poised for explosive growth, so teams should iterate quickly to capture market opp...Show more

Exercise caution when evaluating emerging AI trends—prominent discourse doesn't guarantee maturity or fit, so return to fundamentals and investigate d...Show more

Cameron Rohn observes the inherent trade-off between minimizing harmful outputs like self-harm or suicidal content and preserving adult users’ autonom...Show more

Subscriptions remain for predictability, but AI service economics are migrating toward cost-of-goods-sold execution, minimizing gross margins and refl...Show more

Microsoft believes that autonomous AI agents will become the primary interface across all applications, fundamentally changing user interaction models...Show more

Microsoft’s diverse portfolio—from Bing and Office to Azure and Dynamics—makes it extremely challenging to realign the entire organization around AI-f...Show more