AWS Summit 2026

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This was my second time attending AWS Summit NYC. Last time was in 2024. Like last time I didn’t live blog; it’s not set up well for that. So after the fact summary.

Overview

Like last time, AWS spent a ton of money on this event. They rented out all or most of the Javits Center in NYC (this is where NYC Comic Con is held). They gave coffee/soft drinks and even free lunch. And Dynatrace gave out ice cream.

The event app was great. It gave directions on a map within the building. The directions on the expo floor were particular helpful. (I’m familiar with the real rooms at Javits.

I was pleased with how they did security. They had everyone put their bags through an xray and walk through the advanced detectors they have at Broadway shows and ComiCon. Those go off for laptops and my glasscase. A lot of people had laptops so having all bags go through the xray rather than waiting for people to beep was much smoother. And they were fast weith the xray!

Expo/Keynote

The exhibit hall was large on the third floor with lots of vendors related to cloud. Lots of space and time for networking. They live stream the keynote to the expo stages (where you can listen with headphones or on speakers) and a big screen near the lunch area. The free ticket didn’t come with access to attend the keynote in person but it was nice to be able to wander and listen.

I attended 4 sessions on the smaller stages in the expo. Two had speakers so you could easily hear so I didn’t use the headphones for that. Good if you can’t filter out background noise though. The other two were on a stage without a speaker. The first one I could hear the speaker without headphones (lots of background noise to filter out so most people wore them). The second the speaker didn’t project as much so I didn’t hear him without the headphones.

Chalk talks

There were lots of one hour breakout sessions on the first floor. I went to two “chalk talks” which are supposed to be for experienced people and very technical. They have a whiteboard setup and a screen that projects the whiteboard. Last time I went they used it. The two I went to this time just used a prepared presentation and recorded demo. So like a regular session with more audience questions. Also one session I wanted to go to filled up before I got there.

Hands on sessions

I didn’t go to the hands on sessions this time. Partly because I didn’t want to bring my laptop (i was going to an event after where that would have been hard to watch). And partly from the schedule of what I wanted to see.

My notes

Ok enough about logistics. On to content.

Chalk talk – Improving constituent support with AI agents

  • Solves problem have having to read and analyze (long) docs
  • IDP = intelligent document processing
  • Have multiple agents with expertise in each part
  • Have orchestrator aggregate the finding and present in consolidated view
  • “If it can be done in code, it should be done in code” – re orchestrator doesn’t have to be AI, an be code (presumably written by AI)
  • Showed AI code review of AI code
  • “If Opus can’t read a it; I probably can’t either” – re a diagram’
  • My take: good first session. Even though it wasn’t what I expected in a chalk talk it was detailed and covered a bunch.

Beyond the token: The new economics of scaling enterprise agentic AI

  • “sanbox paralysis” – getting past POCs
  • MAS = multi agent systems
  • “Book of Agents as a Service” – architecture
  • SDLC – AIDLC
  • Maturity model: Opportunity diagnosis (identify high value business bottleneck), implementation, run/scale (prod fleet of agents), transformation (agent first model), orchestrating (MAS)
  • Key: oversight, smart delegation of subtasks, minimize human in loop (phase out over time)
  • New world of risk – prompt injection is now a functional catastrophe and not just a security vulnerability
  • Guardrails need guardrails
  • A2I – amazon augmented ai
  • Matruity jump when lose tolerance for black box/shadow IT. Code can’t just live on dev machine
  • Pricing models: user based (humans), usage based (tokens), KPI based (milestones – ex: claims processed, code deployed, tickets resolved”
  • Model: agents consume from a centarlized license pool and get charged for active reasoning cycles
  • Watch out for agent sprawl. Escape velocity is when you become dependent on a tool even if doesn’t meet guardrails.
  • Reasoning abundance vs token deflation (tokens cost less but costs more from doing more, loops, etc.
  • Right size model – intelligence overkill is a major cost driver
  • My take: Very good session. He covered a lot in half an hour. Very full session; could have used a room and not just been on the show floor

Chalk talk – Building Serverless apps with S3 Vectors

  • Amazon S vectors as easy as S3 to use
  • Subsecond performance
  • Scale to billions of vectors
  • All attributes of S3 like durability
  • Previewed a year ago at AWS summit and GA’d at reinvent
  • UP to 10K similarity results per query
  • Can query with CLI, SDK or AWS Console
  • Billing – pay as you go based on PUT requests, compute, storage, and queries
  • My take: This was not the talk I picked out (that talk was full when I got there. This one was interesting though so I’m glad it was nearby. I did have to leave this one earlier because it started 15 minutes after the session I planned for.

CI/CD meets agentic AI (from GitLab)

  • 21% of time is writing new code
  • 74% of devs want to consolidate their toolchain
  • Demo of DUO (DAP – duo agent platform)
  • Can fix pipeline failures (by pressing button or automatically with agent).
  • Reads logs and repo for context
  • Fixes problem and opens MR for a human to review
  • The recorded demo was of a bad commit to a readme and the fix.
  • After the prepared presentation was done, the speaker asked if we wanted to see a bonus demo of a custom agent. That was live. She injected some problems in code and showed them being detected like a missing paren, logic error and security issue.
  • My take: Recoding the demo made sense because there were some waits that the demo could skip. She commented on them; one step was 11 a time jump.This was a very good session. The speaker was awesome. Great energy and clear. She was also so excited to share the bonus demo and we were excited to see it.

GitLab Duo Agent Platforrm with Amazon Kiro

  • Live demo of Duo. Some similar to the previous one so not rewriting everything.
  • Emphasis on coding is a small part and writing code is not bottleneck.
  • Much time spent on other things like testing.
  • Showed AI determining which items in vulnerability report likely false positives
  • “Most enterprises want a human in the loop”
  • Token is about 1.3 words
  • Orbit – semantic knowledge graph. Stores alongside metadata. Let’s query index.
  • Can query MRs; not just code
  • Can tag agnet in MR comment to interact and create traceable discussions
  • Kiro – compared to claude code, codex. IDE for spec driven dev – I have idea > help me write requirements > help decompose tasks > code tasks
  • My take: I liked the previous session better. I still learned stuff in this one, but I thought it would cover more about Kiro. I asked before the session started and was told this one would cover Kiro. And Kiro was in the name. The speaker mentioned Kiro at most once until the Q&A when I specifically asked about it.

Getting started with Generative AI

  • The beginning of this was introductory which makes sense given the title . I wanted to see what concepts AWS considered important for people to know
  • AI is about probabilistic results. Google maps did that for years before AI with driving estimates.
  • Estimates are ok for some tasks like driving directions and not ok for others like when wheels on plane will touch down if you are a pilot/air traffic control.
  • “Not magical; just another tool”. I had a problem with this analogy because he repeatedly compared gen AI to a calculator. Yes they are both tools. But my *calculator* gives deterministic results.
  • Another analogy that didn’t land was that he said understanding AI is like driving. Can live without knowing it, but…. [I live in NYC and haven’t driven in about 20 years. I get his point that gen AI is important but not a fan of the analogy/
  • Key skills for business leaders: fairness (is solution fair), explanability (what do you want), privacy and security (protect data and models), safety (harmful output), controllability AI behavior), veracity, governance, transparency (ex: does user know talking to a chatbot)
  • Key skills for devs: prompt engineering (compared to talking in a meeeting where things went wrong), RAG, agentic systems, model customization (fine tuning, domain specific data, examples)
  • Kiro.dev – go from AI coding to engineering. Helps create apps using agents. Free tier.
  • Amazon quick – for non coders to automate tasks

PASSED! Jeanne’s Experience Taking the Java 25 Certification Exam 1Z0-831

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Oracle recently announced their new Java 25 Certification Exam 1Z0-831. [Yes, we are working on the certification study guide book] I took it this morning and passed with a 74% (I don’t try for a good score; I try to take it quickly after it comes out. In this case, I took it a few days after getting back from a trip to California. I only slept 5.5 hours last night (got home late from train delays). So I was a bit tired. But I passed and that’s what matters.

If you read my blog post about the Java 21 exam, you know there was significant time pressure. That is fixed on the Java 25 exam. I had sufficient time to go slowly and still had about half an hour left at the end which I could have used to review my answers. (I choose to turn it in without reviewing because I felt a little dizzy; probably from using the computer right when I woke up after insufficient sleep.)

Checking in

Oracle changed how they do exams since the Java 21 exam came out. (You saw a person as proctor.) The new system is described here and much better. I used it when taking Oracle cloud exams and it is the system in use now for the Java 25 exam. It comes with an online whiteboard.

The exam

While there were still some long questions, it was faster to read the code. It was either read some code and state the output (so only one set of code to read) or multiple answers with code where it was easier to tell the differences. Also there were less long questions so I didn’t feel time pressure.

Looking back I had 16 minutes left after the Java 21 exam. While I had more time left over here, the big difference is I went super slow this time while last time I had to rush to get that time. I knew I was tired and didn’t want to make silly mistakes.

About 5 questions took about 10 seconds to load. That feels like forever during an exam! And it was before 8am in the morning local time so it wasn’t a lot of people using the internet. I hadn’t had that problem on past exams.

For content, I got a good mix of questions spanning the objectives. Not as many Java 22-25 questions as I expected but that could be luck of the draw.

After the exam

I removed the “Secure Companion” app and Proctorio Chrome plugin. from my machine. It has a lot of power so I like it not being there.

I tried going to the CertView page to get my badge but got a 502 error. Will try again in the future. I used Chrome as Safari on Mac didn’t let me expand the menus in the past.

To see my exam details:

  • Expand “Exam Results” on left navigation
  • Click “Exam History” on left navigation
  • Click “Results” on this exam on the right side
  • This downloads a PDF showing which objectives you got a question wrong on

For credentials, expand “Credential Management” on left navigation. You can then download a certificate or badge. There are also links to post on LinkedIn or email a link to verify your credential. I then went on Linked in and added a credential including the credential URL.

2026 buying us open tickets

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Last year I wrote a blog complaining about my failed attempt to buy US Open tickets. It’s a year later. Time to blog about it went this year!

Grounds Pass

knew from last year that you had to be on ticketmaster a few minutes before 9am to get a random spot in the queue when it opened at 9am. I was. I got number 48! Lucky me.!

I knew I wanted to buy grounds passes for one day and Arthur Ashe tickets for another. And from last year, I knew that the grounds passes would sell out faster. So I started with grounds. I put them in my cart and it worked. (Last year, they sold out while I was putting them in my cart.) I wasn’t confident that navigating to the Ashe tickets would keep these grounds passes so I took the risk of checking out with just those. Worked great. I gave my American Express card. (you have to pay by amex as it was the amex presale.

I got prompted for an “Amex Safekey Verification Code” which was a number texted to me. Last year, i didn’t get this for Amex. I did get it for another card whre the code didn’t arrive so this was an improvement.

Ashe Ticket

Then I went to buy my Ashe ticket. I did get dumped in the queue again. I don’t know what would have happened if I went to this page with the grounds passes in my shopping cart but I was too afraid to find out. This time I was number 13,567 in the queue. That was just over 90 minutes of waiting. (Last year 2200 was 40 minutes of waiting so definitely a faster rate.) This was fine; I kept it on one screen while I did work until it was my turn.

There was a good selection of tickets at different price points, sections, heights when I got in. Last year, I was annoyed that you only get told the section and row numbers (vs the actual seat number) when buying the ticket. I’m not a fan of that system and it is back. I suppose this helps them manage concurrency but as a customer I like knowing which seat number. In particular, I like to sit in the vicinity of the aisle so I don’t have to climb over a dozen people when it is time to go to tthe bathroom. I wound up with a seat 5 away from the aisle which I’m ok with. But It feels like gambling.

Conclusion to last year

I was able to buy the grounds passes closer to the time when they released more. But it was a project to keep checking. Also my friend and I monitored the morning of to see when the “resellers” would drop their prices. After all, we live nearby so good information for future years. (I won’t pay above face value but if they dropped it to that point, I would.) Moot point. They did not drop the prices. Even 5 minutes before the seats could no longer be sold they were well about face value. At which point their value went to $0 and the “resellers” lost all remaining value. They must make enough from people willing to pay inflated prices that it is worth eating the loss so people know they prices won’t come down.