๐ฏ From Chaos to Control: Building Predictable AI Agents That Get Smarter Over Time
๐ฏ From Chaos to Control: Building Predictable AI Agents That Get Smarter Over Time
Agentic systems are incredibly flexible, but ad-hoc code generation means unpredictable results and wasted resources. How do we fix this without losing the magic? The answer lies in toolsโprebuilt, tested, reusable components that make your AI agents more capable, reliable, and cost-efficient with every interaction.
With the right approach, your agents can become smarter and more efficient over time. Dive deep in the article below.
๐ฑ ๐๐ฟ๐ด๐ต - ๐ ๐ ๐๐ ๐๐ด๐ฒ๐ป๐ ๐ฑ๐ฒ๐น๐ฒ๐๐ฒ๐ฑ ๐ฎ๐น๐น ๐บ๐ ๐ณ๐ถ๐น๐ฒ๐!!!! Worried about AI agents running amok with your data? B
๐ฑ ๐๐ฟ๐ด๐ต - ๐ ๐ ๐๐ ๐๐ด๐ฒ๐ป๐ ๐ฑ๐ฒ๐น๐ฒ๐๐ฒ๐ฑ ๐ฎ๐น๐น ๐บ๐ ๐ณ๐ถ๐น๐ฒ๐!!!! Worried about AI agents running amok with your data? Before panicking, consider this: we’ve been solving permission and access control problems for decades with human coworkers. Let’s apply those same principles to our new AI teammates and find the right balance between agency and control. #AIAgents #FutureOfWork
Argh - My AI Agent deleted all my files
๐ฑ “Argh - My AI Agent deleted all my files!!!!”
When was the last time one of your co-workers deleted an important file from your desktop?
I would hope it has been a long time ago and quite possibly never.
๐ฅ๏ธ Even at the time we used shared computers, home directories have been separated.
There was a notion of shared folders or network folders or whatever nomenclature the system you were using. So in order to provide access to files to coworkers, you would need to take the decision first to upload it to a shared folder.
Jeff Harman in on fireย - pun intendedย in this talk '๐๐ช๐ฆ ๐ฟ๐ฒ:๐๐ป๐๐ฒ๐ป๐ ๐ฎ๐ฌ๐ฎ๐ฑ - ๐๐ฑ๐ง๐ฒ๐ฐ๐ต
Jeff Harman in on fireย - pun intendedย in this talk “๐๐ช๐ฆ ๐ฟ๐ฒ:๐๐ป๐๐ฒ๐ป๐ ๐ฎ๐ฌ๐ฎ๐ฑ - ๐๐ฑ๐ง๐ฒ๐ฐ๐ต ๐๐ป๐ป๐ผ๐๐ฎ๐๐ถ๐ผ๐ป ๐๐ถ๐๐ต ๐๐-๐๐ฟ๐ถ๐๐ฒ๐ป ๐๐ฒ๐๐ฒ๐น๐ผ๐ฝ๐บ๐ฒ๐ป๐ ๐ณ๐ผ๐ฟ ๐๐ฟ๐ฎ๐ป๐ฑ ๐๐ด๐ฒ๐ป๐๐ (๐๐ก๐๐ฏ๐ฏ๐ฏ๐ฐ)” [1]ย while explaining how AdTech teams can use AWSโs AI-Driven Development Lifecycle (AI-DLC) to build production-grade โbrand agentsโ for advertisers in about five days instead of months.[1]
Super interesting talk for everyone in advertising to get a better understanding of not only why agents will impact your business, but also build those efficiently.
Amazing keynote by Swami Sivasubramanian. At least the first 40 minutes are super useful, even if yo
Amazing keynote by Swami Sivasubramanian. At least the first 40 minutes are super useful, even if you are not super interested in new service launches. Swami nicely breaks down how AI agents and Agentic AI are relevant, how they work and what are common challenges to adopt them. Being at an AWS keynote, he obviously also explains how you can implement your own Agents successfully.
William Brennan, VP Enterprise Technology at Blue Origin, talked intensively about their journey to take systems built by AI Agents, into space. Well, not everyone flies into space, but a lot of Blue Origin’s insights can be adopted to any enterprise. Some key aspects I noted are:
๐ช๐ต๐ฎ๐ ๐ต๐ฎ๐ฝ๐ฝ๐ฒ๐ป๐ฒ๐ฑ ๐๐ต๐ถ๐ ๐๐ฒ๐ฎ๐ฟ ๐๐ถ๐๐ต ๐๐ต๐ฒ ๐ด๐ฒ๐ป๐ฒ๐ฟ๐ฎ๐๐ถ๐๐ฒ ๐๐ ๐๐ต๐ถ๐ป๐ด๐ ๐ฎ๐ ๐๐ป๐๐ต๐ฟ๐ผ๐ฝ๐ถ๐ฐ? ๐ช๐ต๐ฎ๐ ๐ถ๐ ๐ฐ๐ผ๐บ๐ถ
๐ช๐ต๐ฎ๐ ๐ต๐ฎ๐ฝ๐ฝ๐ฒ๐ป๐ฒ๐ฑ ๐๐ต๐ถ๐ ๐๐ฒ๐ฎ๐ฟ ๐๐ถ๐๐ต ๐๐ต๐ฒ ๐ด๐ฒ๐ป๐ฒ๐ฟ๐ฎ๐๐ถ๐๐ฒ ๐๐ ๐๐ต๐ถ๐ป๐ด๐ ๐ฎ๐ ๐๐ป๐๐ต๐ฟ๐ผ๐ฝ๐ถ๐ฐ? ๐ช๐ต๐ฎ๐ ๐ถ๐ ๐ฐ๐ผ๐บ๐ถ๐ป๐ด ๐ป๐ฒ๐ ๐?
The week(s) after re:invent are typically the time, where a pile of very good content videos pile up at my end and I have both a hard and fun time to get through this.
Today the “๐๐ช๐ฆ ๐ฟ๐ฒ:๐๐ป๐๐ฒ๐ป๐ ๐ฎ๐ฌ๐ฎ๐ฑ - ๐ช๐ต๐ฎ๐ ๐๐ป๐๐ต๐ฟ๐ผ๐ฝ๐ถ๐ฐ ๐๐ฒ๐ฎ๐ฟ๐ป๐ฒ๐ฑ ๐๐๐ถ๐น๐ฑ๐ถ๐ป๐ด ๐๐ ๐๐ด๐ฒ๐ป๐๐ ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฑ (๐๐๐ ๐ฎ๐ณ๐ณ” ended up on the top of the pile and turned the time on the rowing machine in the gym to a fun learning experience. After all it’s a level 200 session - should be able to follow it during a casual workout, right?
๐๏ธ In a fantastic interview 'How AI will change software engineering โ with Mart
๐๏ธ In a fantastic interview “How AI will change software engineering โ with Martin Fowler” at the Pragmatic Engineer Podcast [1], Martin Fowler highlights the non-determinism introduced by Agentic AI as the big challenge for adoption. So big of a challenge that he compares it to the evolution from assembler code to higher-level programming languages.
๐ค Indeed, I see a lot of customers struggling with this non-determinism. What is correct? How do I evaluate a system? What about cascading effects in multi-agent systems?
Working in monetisation, advertising or markteting and youโre not sure what kind of use cases can be
Working in monetisation, advertising or markteting and youโre not sure what kind of use cases can be enhanced with AI Agents? Found your use case but struggle with implementation as too many choices to be made?
This solution guidance for advertising agents on AWS has you covered. Source code included!
So great to see that published. Many folks at #ibc where asking for access :) - awesome work Zelle Steyn and team!
โก ๐๐ฒ๐๐ผ๐ป๐ฑ ๐๐ต๐ฎ๐๐ฏ๐ผ๐๐: ๐๐ผ๐ ๐๐ผ๐ ๐๐๐๐ผ๐บ๐ผ๐๐ถ๐๐ฒ ๐ฎ๐ป๐ฑ ๐๐ฟ๐๐๐ฎ ๐๐ฟ๐ฒ ๐๐๐ถ๐น๐ฑ๐ถ๐ป๐ด ๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐๐ถ๐ผ๐ป ๐๐ ๐๐ด๐ฒ๐ป๐๐ ๐ง๐ต๐ฎ๐ ๐๐ฐ๐๐๐ฎ๐น๐น๐ ๐ช๐ผ๐ฟ๐ธ
โก ๐๐ฒ๐๐ผ๐ป๐ฑ ๐๐ต๐ฎ๐๐ฏ๐ผ๐๐: ๐๐ผ๐ ๐๐ผ๐ ๐๐๐๐ผ๐บ๐ผ๐๐ถ๐๐ฒ ๐ฎ๐ป๐ฑ ๐๐ฟ๐๐๐ฎ ๐๐ฟ๐ฒ ๐๐๐ถ๐น๐ฑ๐ถ๐ป๐ด ๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐๐ถ๐ผ๐ป ๐๐ ๐๐ด๐ฒ๐ป๐๐ ๐ง๐ต๐ฎ๐ ๐๐ฐ๐๐๐ฎ๐น๐น๐ ๐ช๐ผ๐ฟ๐ธ
In this brand new blog post Brad Abrams and Jawhny Cooke showcase why Claude and Bedrock AgentCore work better together. Highly recommend to dive deeper into the blog post.
๐ฆ๐ต๐ผ๐ฟ๐ ๐๐๐บ๐บ๐ฎ๐ฟ๐: โข ๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐๐ถ๐ผ๐ป-๐ฅ๐ฒ๐ฎ๐ฑ๐ ๐๐ป๐ณ๐ฟ๐ฎ๐๐๐ฟ๐๐ฐ๐๐๐ฟ๐ฒ ๐ ๐ฒ๐ฒ๐๐ ๐๐ฑ๐๐ฎ๐ป๐ฐ๐ฒ๐ฑ ๐๐: AgentCore eliminates months of building infrastructure (session management, credential vaults, scaling logic), allowing teams to focus on business value while Claude Sonnet 4.5 provides state-of-the-art reasoning and autonomous operation for up to 8 hours
๐๐ ๐๐ด๐ฒ๐ป๐๐ ๐ป๐ฒ๐ฒ๐ฑ ๐น๐ฎ๐ฝ๐๐ผ๐ฝ๐ - ๐น๐ถ๐ธ๐ฒ ๐ต๐๐บ๐ฎ๐ป ๐๐๐๐ฑ๐ฒ๐ป๐๐ ...
๐๐ ๐๐ด๐ฒ๐ป๐๐ ๐ป๐ฒ๐ฒ๐ฑ ๐น๐ฎ๐ฝ๐๐ผ๐ฝ๐ - ๐น๐ถ๐ธ๐ฒ ๐ต๐๐บ๐ฎ๐ป ๐๐๐๐ฑ๐ฒ๐ป๐๐ …
This week I had the pleasure of listening to Matt Bell’s presentation on Claude models. He covered the short but impressive history of Claude and the current state of affairs.
๐ฏ ๐ง๐๐ผ ๐พ๐๐ผ๐๐ฒ๐ ๐๐๐ผ๐ผ๐ฑ ๐ผ๐๐ ๐๐ผ ๐บ๐ฒ:
ย 1๏ธโฃ “๐๐ถ๐ธ๐ฒ ๐๐ผ๐ ๐ฎ๐น๐๐ฎ๐๐ ๐ด๐ถ๐๐ฒ ๐๐ผ๐๐ฟ ๐ฒ๐บ๐ฝ๐น๐ผ๐๐ฒ๐ฒ๐ ๐ฎ ๐น๐ฎ๐ฝ๐๐ผ๐ฝ, ๐๐ผ๐ ๐๐ต๐ผ๐๐น๐ฑ ๐ด๐ถ๐๐ฒ ๐๐น๐ฎ๐๐ฑ๐ฒ ๐ฎ ๐๐ถ๐ฟ๐๐๐ฎ๐น ๐บ๐ฎ๐ฐ๐ต๐ถ๐ป๐ฒ.”
ย 2๏ธโฃ “๐ช๐ฒ’๐ฟ๐ฒ ๐ฑ๐ผ๐ถ๐ป๐ด ๐๐ฒ๐น๐น ๐๐ถ๐๐ต ๐บ๐ผ๐ฑ๐ฒ๐น ๐ฝ๐ฒ๐ฟ๐ณ๐ผ๐ฟ๐บ๐ฎ๐ป๐ฐ๐ฒ, ๐ฏ๐๐ ๐๐๐ถ๐ป๐ด ๐๐ผ๐ผ๐น๐ ๐ฎ๐ป๐ฑ ๐ผ๐๐ต๐ฒ๐ฟ ๐ฎ๐ฑ๐ฑ-๐ผ๐ป๐ ๐ฏ๐ฟ๐ถ๐ป๐ด๐ ๐บ๐๐ฐ๐ต ๐บ๐ผ๐ฟ๐ฒ ๐ฝ๐ฒ๐ฟ๐ณ๐ผ๐ฟ๐บ๐ฎ๐ป๐ฐ๐ฒ ๐ฏ๐ผ๐ผ๐๐.”