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This Dot AI Field Notes - Anatomy of a Coding Harness
A coding agent is not magic, it’s a loop. We call this a harness. The harness is a deterministic layer of code that wraps an LLM....
May 12, 2026
1 min
AI Is Speeding Up Development. But Where Are the New Bottlenecks?
AI is accelerating development, but it’s also exposing everything else that’s broken. At the Leadership Exchange, leaders unpacked how AI is reshaping the SDLC and what organizations need to address beyond just coding to make adoption successful. Moderated by Rob Ocel, VP of Innovation at This Dot Labs, the panel featured Itai Gerchikov at Anthropic and Harald Kirschner, Principal Product Manager for GitHub Copilot & VS Code at Microsoft. Panelists explored the current state of AI adoption across the software development lifecycle and shared practical insights into how organizations can effectively integrate AI tools. Panelists discussed how companies are investing in AI tools, skills, and managed competency programs to support developers. While AI can dramatically accelerate coding, the panel emphasized that adoption affects every stage of the SDLC. Bottlenecks now appear in testing, DevOps, product delivery, and marketing as AI speeds up development. Organizations that address technical debt and process inefficiencies are better positioned to extract maximum value from AI tools. The conversation also focused on opportunities and risks. Security, governance, and workforce education were highlighted as critical factors for adoption. Panelists stressed that AI initiatives should be aligned with broader business goals rather than pursued in isolation. They noted that companies experimenting at the cutting edge need to consider organizational readiness just as carefully as technical capabilities. Panelists also explored how leading organizations are navigating the early stages of adoption. Those ahead of the curve are using structured experimentation, prioritizing process improvements, and continuously evaluating outcomes to refine their AI strategies. Learning from these early adopters allows other organizations to anticipate emerging trends and prepare for the next phase of AI adoption rather than simply replicating past approaches. Key Takeaways - Investing in AI skills and tools should be done thoughtfully, with clear alignment to business objectives. - Examining the full SDLC helps identify bottlenecks that AI may accelerate or expose. - Organizations can gain a competitive advantage by learning from early adopters and planning for where AI adoption is heading. AI adoption is not just a technical initiative; it is a strategic transformation that requires attention to people, process, and technology. Organizations that balance innovation with operational discipline will be best positioned to capture the full potential of AI across the software lifecycle. Seeing similar challenges in your own SDLC? Let’s compare notes. Join us at an upcoming Leadership Exchange or reach out to continue the conversation. Tracy can be reached at tlee@thisdot.co....
Mar 27, 2026
2 mins
Making AI Deliver: From Pilots to Measurable Business Impact
A lot of organizations have experimented with AI, but far fewer are seeing real business results. At the Leadership Exchange, this panel focused on what it actually takes to move beyond experimentation and turn AI into measurable ROI. Over the past few years, many organizations have experimented with AI, but the challenge today is translating experimentation into measurable business value. Moderated by Tracy Lee, CEO at This Dot Labs, panelists featured Dorren Schmitt, Vice President IT Strategy & Innovation at Allen Media Group, Greg Geodakyan, CTO at Client Command, and Elliott Fouts, CAIO & CTO at This Dot Labs. Panelists discussed how companies are moving from early AI experiments to initiatives that deliver real results. They began by examining how experimentation has evolved over the past year. While many organizations did not fully utilize AI experimentation budgets in 2025, 2026 is showing a shift toward more intentional investment. Structured budgets and clearly defined frameworks are enabling companies to explore AI strategically and identify initiatives with high potential impact. The conversation then turned to alignment and ROI. Panelists highlighted the importance of connecting AI projects to corporate strategy and leadership priorities. Ensuring that AI initiatives translate into operational efficiency, productivity gains, and measurable business impact is essential. Companies that successfully align AI efforts with organizational goals are better equipped to demonstrate tangible outcomes from their investments. Moving from pilots and proofs of concept to production was another major focus. Governance, prioritization, and workflow integration were cited as essential for scaling AI initiatives. One panelist shared that out of nine proofs of concept, eight successfully launched, resulting in improvements in quality and operational efficiency. Panelists also explored the future of AI within organizations, including the potential for agentic workflows and reduced human-in-the-loop processes. New capabilities are emerging that extend beyond coding tasks, reshaping how teams collaborate and how work is structured across departments. Key Takeaways - Structured experimentation and defined budgets allow organizations to explore AI strategically and safely. - Alignment with business priorities is essential for translating AI capabilities into measurable outcomes. - Governance and workflow integration are critical to moving AI initiatives from pilot stages to production deployment. Successfully leveraging AI requires a balance between experimentation, strategic alignment, and operational discipline. Organizations that approach AI as a structured, measurable initiative can capture meaningful results and unlock new opportunities for innovation. Curious how your organization can move from AI experimentation to real impact? Let’s talk. Reach out to continue the conversation or join us at an upcoming Leadership Exchange. Tracy can be reached at tlee@thisdot.co....
Mar 27, 2026
2 mins
What does it actually look like to build software with AI today? Not in theory, but in practice.
What does it actually look like to build software with AI today? Not in theory, but in practice. At the Leadership Exchange, this was the question at the center of the Developer Panel, where leaders from across the industry unpacked what’s really changing inside engineering teams and what organizations need to do right now to keep up. The Developer Panel at the Leadership Exchange explored the cutting edge of AI in software engineering and examined what organizations should focus on today to prepare for the future. Moderated by Jeff Cross, Co-Founder & CEO at Nx, the panel featured Victor Savkin, Cofounder & CTO at Nx, Alex Sover, Vice President of Engineering at OpenAP, Brent Zucker, Senior Director of Engineering at Visa, and Jonathan Fontanez, AI Engineering Lead at This Dot Labs. Panelists shared insights into how AI is transforming the software development lifecycle and how teams can adopt tools effectively while preparing for organizational change. Panelists discussed emerging workflows, including CI-in-the-loop, agentic healing, and context engineering. They examined how validation, code reviews, and PRDs are evolving alongside AI capabilities and how teams are integrating external sources such as production traces to improve quality and reliability. The discussion also covered what the next generation of agentic tools might look like and how these capabilities will shape engineering practices in the near future. Adoption of AI comes with challenges. Teams often rely on plugins or extensions without foundational understanding, and individual contributors may fear displacement. Panelists emphasized that education, governance, and skill-building are essential for teams to manage AI agents effectively while maintaining quality. They also highlighted the need to standardize workflows and ensure organizational alignment to fully leverage AI capabilities. The conversation extended beyond technical challenges to organizational implications. Panelists discussed how teams can avoid issues like Conway’s Law, manage distributed teams effectively, and evolve engineering practices alongside AI adoption. Leadership and management strategies play a crucial role in ensuring that AI integration delivers meaningful outcomes while maintaining efficiency and alignment with business objectives. Key Takeaways - AI workflows require both technical and organizational preparation. - Education, governance, and skill development are essential for successful implementation. - Forward-looking teams are rethinking validation, CI pipelines, and context management to fully leverage agentic AI. The discussion highlighted that adopting AI at the cutting edge is not just about new tools - it is about rethinking processes, workflows, and organizational culture. Companies that embrace this holistic approach are most likely to succeed in leveraging AI to its full potential. Are you interested in more conversations like this? Message us for an invite to the next, or for a private discussion around these topics. Tracy can be reached at tlee@thisdot.co....
Mar 27, 2026
2 mins
![Quo v[AI]dis, Tech Stack? cover image](https://images.ctfassets.net/zojzzdop0fzx/28QIo74U7Nh8vFgxM7zrlJ/8b97153a1641a96380c6e9bfa32c1f95/Quo_v-AI-dis__Tech_Stack.png?fm=webp&w=3840&q=75)
Quo v[AI]dis, Tech Stack?
The article explores how AI is no longer just speeding up coding - it’s actively reshaping the choices we make as developers. From self-reinforcing loops around popular stacks like React and Node.js to AI-generated apps....
Aug 7, 2025
11 mins
Roo Custom Modes
Roo Code is an extension for VS Code that provides agentic-style AI code editing functionality. You can configure Roo to use any LLM model and version you want by providing API keys....
Jun 13, 2025
6 mins
What Sets the Best Autonomous Coding Agents Apart?
Autonomous coding agents are no longer experimental, they are becoming an integral part of modern development workflows, redefining how software is built and maintained....
Jun 3, 2025
4 mins
Increasing development velocity with Cursor
Boost your coding efficiency with Cursor, an AI-powered VSCode fork. Learn how features like Autocomplete, Ask, and Agent can streamline development, automate tasks, and enhance productivity....
Apr 18, 2025
11 mins
“Recognize leadership behavior early. Sometimes people don’t even realize it in themselves…” Kelly Vaughn on Product Leadership, Creating Pathways for Women in Tech, & Conferences
Some leaders build products. Some lead engineering teams. Kelly Vaughn is doing both. As Director of Engineering at Spot AI—a company building video intelligence software—Kelly recently expanded her role to oversee both Product and Engineering for their VMS offering. That shift means juggling strategy, execution, and team development, all while helping others step confidently into leadership themselves. And yes, she still finds time to speak at conferences and answer DMs from people navigating the same transitions she once did. We spoke with Kelly about spotting leadership potential early, why ambiguity doesn’t have to feel chaotic, and the lesson she learned the hard way about managing up. Stepping into Product Leadership Kelly’s new title might look like a promotion on paper, but the shift is more philosophical than anything. > “Engineering leadership is about execution,” she says. “Product leadership is about defining why we’re building something in the first place.” Now leading Product and Engineering for Spot AI’s VMS product, she’s talking to customers, researching market trends, and making smart bets on where to invest next. It’s a role she’s clearly energized by. > “I’m really looking forward to dedicating time to shaping our product’s future.” Thriving in Ambiguity Some people panic when problems are fuzzy or undefined. Others use it as fuel. > “There are two key traits I see in people who handle ambiguity well,” Kelly says. “They stay calm under stress, and they know how to form a hypothesis from a vague problem statement.” That means asking the right questions, taking action quickly, and being totally okay with pivoting when something doesn’t pan out. It’s no surprise that these same traits overlap with great product thinking—a mindset she’s now leaning into more than ever. > “I do some of my best work when navigating uncertainty,” she adds. Read Kelly’s blog on embracing ambiguity in Product! Creating Leadership Pathways for Women in Tech When asked how leaders can create more leadership pathways for women in software engineering, Kelly stressed that it is not a passive process. > “Senior leaders need to be proactive,” Kelly says. “That starts with identifying and addressing bias across hiring, promotions, and day-to-day interactions.” She emphasizes psychological safety—so women feel confident advocating for themselves and others. But she also knows not everyone feels ready to raise their hand. > “Don’t wait for someone to ask for a title change or a growth opportunity. Recognize leadership behavior early. Sometimes people don’t even realize it in themselves yet.” On Stage, In Real Life Kelly’s no stranger to the tech conference circuit—often giving talks on engineering leadership and team growth. Her biggest source of inspiration? Conversations with people trying to make the leap into leadership. > “I might use the same slide deck at three conferences,” she says, “but the talk itself will be different every time.” Rather than sticking to a script, she likes to share recent examples from her own work, tailoring the delivery to the audience in front of her. It keeps things relevant, grounded, and never too polished. Between setting product strategy, mentoring the next generation of leaders, and hopping from one tech conference to the next, Kelly Vaughn is showing what it means to lead with clarity—even when things are unclear. She’s not here to tell you it’s easy. But she will tell you it’s worth it. Connect with Kelly Vaughn on Bluesky. Sign up for Kelly Vaughn’s Newsletter! Sticker Illustration by Jacob Ashley....
Apr 4, 2025
3 mins
“It Sounds a Little Dystopian, But Also Kind of Amazing”: Conversations on Long Term AI Agents and "Winning" Product Hunt with Ellie Zubrowski
Ellie Zubrowski doesn’t walk a traditional path. In the three years since graduating from a university program in Business Administration, she biked across the U.S., studied Kung Fu in China, learned Mandarin just for fun, and completed the #100DaysOfCode challenge after deciding she wanted a career switch. That same sense of curiosity and willingness to jump into the unknown now fuels her work as a Developer Advocate at Pieces, where she leads product launches, mentors job seekers, and helps developers learn how to best leverage Pieces’ Long-Term Memory Agent. Her journey into tech was guided not just by a want to learn how to code and break into the industry, but by a fascination with the structure of language itself. > “There are so many parallels between human languages and programming languages,” she says. “That realization really made me fall in love with software.” > We spoke with Ellie about launching a #1 Product Hunt release, her predictions for AI agents, and why conferences don’t have to break your budget. Launching LTM-2 to the Top of Product Hunt Recently, Ellie led the launch of Pieces’ Long-Term Memory Agent (LTM-2), which took the top spot on Product Hunt—a major win for the team and their community. > “I’m super competitive,” she admits. “So I really wanted us to win.” The launch was fully organic—no paid promotions, just coordinated team efforts, a well-prepared content pipeline, and an ambassador program that brought in authentic engagement across X, Discord, and Reddit. She documented their entire strategy in this blog post, and credits the success not just to good planning but to a passionate developer community that believed in the product. Following a successful performance at Product Hunt, Ellie is committed to keeping Pieces’ user community engaged and contributing to its technological ecosystem. > “Although I’m still fairly new to DevRel (coming up on a year at Pieces!), I think success comes down to a few things: developer adoption and retention, user feedback, community engagement, and maintaining communication with engineering.” Why AI Agents Are the Next Big Thing Ellie sees a major shift on the horizon: AI that doesn’t wait for a prompt. > “The biggest trend of 2025 seems to be AI agents,” she explains, “or AI that acts proactively instead of reactively.” Until now, most of us have had to tell AI exactly what to do—whether that’s drafting emails, debugging code, or generating images. But Ellie imagines a near future where AI tools act more like intelligent teammates than assistants—running locally, deeply personalized, and working in the background to handle the repetitive stuff. > “Imagine something that knows how you work and quietly handles your busy work while you focus on the creative parts,” she says. “It sounds a little dystopian, but also kind of amazing.” Whether we hit that level of autonomy in 2025 or (likely) have to wait until 2026, she believes the move toward agentic AI is inevitable—and it’s changing how developers think about productivity, ownership, and trust. You can read more of Ellie’s 2025 LLM predictions here! The Secret to Free Conferences (and Winning the GitHub Claw Machine) Ellie will be the first to tell you: attending a tech conference can be a total game-changer. “Attending my first tech conference completely changed my career trajectory,” she says. “It honestly changed my life.” And the best part? You might not even need to pay for a ticket. > “Most conferences offer scholarship tickets,” Ellie explains. “And if you’re active in dev communities, there are always giveaways. You just have to know where to look.” In her early days of job hunting, Ellie made it to multiple conferences for free (minus travel and lodging)—which she recommends to anyone trying to break into tech. Also, she lives for conference swag. One of her all-time favorite moments? Winning a GitHub Octocat from the claw machine at RenderATL. > “She’s one of my prized possessions,” Ellie laughs. Proof here. 🐙 Her advice: if you’re even a little curious about going to a conference—go. Show up. Say hi to someone new. You never know what connection might shape your next step. Ellie’s Journeys Away from her Desk Earlier this year, Ellie took a break from product launches and developer events to visit China for Chinese New Year with her boyfriend’s family—and turned the trip into a mix of sightseeing, food adventures, and a personal mission: document every cat she met. (You can follow the full feline thread here 🐱) The trip took them through Beijing, Nanjing, Taiyuan, Yuci, Zhùmǎdiàn, and Yangzhou, where they explored palaces, museums, and even soaked in a hot spring once reserved for emperors. > “Fancy, right?” Ellie jokes. But the real highlight? The food. > “China has some of the best food in the world,” she says. “And lucky for me, my boyfriend’s dad is an amazing cook—every meal felt like a five-star experience.” What’s Next? With a YouTube series on the way, thousands of developers reached through her workshops, and an eye on the next generation of AI tooling, Ellie Zubrowski is loving her experience as a developer advocate. Follow @elliezub on X to stay in the loop on her work, travels, tech experiments, and the occasional Octocat sighting. She’s building in public, cheering on other devs, and always down to share what she’s learning along the way. Learn more about Pieces, the long-term LLM agent. Sticker Illustration by Jacob Ashley...
Mar 28, 2025
4 mins
“ChatGPT knows me pretty well… but it drew me as a white man with a man bun.” – Angie Jones on AI Bias, DevRel, and Block’s new open source AI agent “goose”
Angie Jones, VP of Developer Relations at Block, champions developer advocacy, AI ethics, and leadership. She’s leading discussions on AI governance, bias in career tools, and *goose*, an open-source AI assistant for developers....
Mar 13, 2025
4 mins
How to build an AI assistant with OpenAI, Vercel AI SDK, and Ollama with Next.js
Learn how to run Llama 3.1 locally in a Next.js app, send audio to it, and play responses back to users....
Sep 27, 2024
8 mins
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