We made it— 300 episodes of This Is Woman’s Work ! And we’re marking this milestone by giving you something that could seriously change the game in your business or career: the skill of pitching yourself effectively. Whether you’re dreaming of being a podcast guest, landing a speaking gig, signing a client, or just asking for what you want with confidence—you’re already pitching yourself, every day. But are you doing it well? In this milestone episode, Nicole breaks down exactly how to pitch yourself to be a podcast guest … and actually hear “yes.” With hundreds of pitches landing in her inbox each month, she shares what makes a guest stand out (or get deleted), the biggest mistakes people make, and why podcast guesting is still one of the most powerful ways to grow your reach, authority, and influence. In This Episode, We Cover: ✅ Why we all need to pitch ourselves—and how to do it without feeling gross ✅ The step-by-step process for landing guest spots on podcasts (and more) ✅ A breakdown of the 3 podcast levels: Practice, Peer, and A-List—and how to approach each ✅ The must-haves of a successful podcast pitch (including real examples) ✅ How to craft a pitch that gets read, gets remembered, and gets results Whether you’re new to pitching or want to level up your game, this episode gives you the exact strategy Nicole and her team use to land guest spots on dozens of podcasts every year. Because your voice deserves to be heard. And the world needs what only you can bring. 🎁 Get the FREE Podcast Pitch Checklist + Additional Information on your Practice Group, Peer Group, and A-List Group Strategies: https://nicolekalil.com/podcast 📥 Download The Podcast Pitch Checklist Here Related Podcast Episodes: Shameless and Strategic: How to Brag About Yourself with Tiffany Houser | 298 How To Write & Publish A Book with Michelle Savage | 279 How To Land Your TED Talk and Skyrocket Your Personal Brand with Ashley Stahl | 250 Share the Love: If you found this episode insightful, please share it with a friend, tag us on social media, and leave a review on your favorite podcast platform! 🔗 Subscribe & Review: Apple Podcasts | Spotify | Amazon Music…
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Ep25: Github Actions + AI Coding Assistant
Manage episode 452651195 series 3579839
Contenido proporcionado por jmhreif. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente jmhreif o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
In this episode, hear some positive tech experiences from the week: the upgrade from GitHub Actions (upload/download artifact) to v4 through a 3rd party repo, and the new AI coding assistant feature in IntelliJ IDEA.
40 episodios
CompartirManage episode 452651195 series 3579839
Contenido proporcionado por jmhreif. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente jmhreif o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
In this episode, hear some positive tech experiences from the week: the upgrade from GitHub Actions (upload/download artifact) to v4 through a 3rd party repo, and the new AI coding assistant feature in IntelliJ IDEA.
40 episodios
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Fresh from the Arc of AI conference , I’m unpacking the biggest insights that stuck with me—ranging from the extremes of AI’s capabilities to the deeper implications for how we build and maintain our tech systems. I’ll also share a new blog post and code repo I published on loading data into Pinecone, some next-gen tools I’m eyeing, and thoughts on a great article from the Redis blog about why vector databases aren’t enough . Navigate the evolving landscape of LLMs, generative AI, and modern infrastructure with me in this episode.…
In this podcast episode, hear about my hands-on experience ( code repository on Github ) understanding the importance of using the same embedding models for both creating and searching vector embeddings in databases and how mismatched models can lead to poor search results. I also pull highlights from an article with advice for those interested in blogging , and how it particularly relates to my own approach to tech blogging.…
In this episode, I continue my journey with vector databases, integrating Pinecone , Neo4j , and Spring AI . While making some progress, I also encountered hurdles, such as evolving APIs and the unique architecture of vector stores. Next, I share insights from an article on contributing to open-source projects , how it can accelerate your career and enhance both your technical and soft skills. From picking the right project to building credibility within the community, it's a series of steps that gets better with time and practice!…
In this episode, I discuss my challenges exploring vector databases for an upcoming demo. From what is a vector database to integration issues, hear how I tried a few different approaches with limited success and discover the surprising one with the most promise. I also explore Microsoft's "Lazy Graph RAG" approach, which seems to trade one challenge for another but could be valuable in certain cases.…
This week, I explored the Javalin Java framework and project decisions I'm trying to make. I also answer: What exactly does a Developer Advocate/Evangelist/Devrel do? Finally, I reflect on an article on balancing digital consumption with actual productivity.
In this episode, there are two topics I'm looking forward to diving deeper into: vector databases and AI agents. I'm particularly interested in understanding how vector databases work, how they work with data, and their role in AI applications. Then I share my thoughts on Anthropic’s article about Building AI Agents , which discusses their varying definitions—from simple workflows to fully autonomous systems—and provides practical examples. The article highlights the importance of starting simple, adding complexity only as needed.…
In this podcast episode, hear my process of preparing for an upcoming conference with insights on how outlines enhance presentations and blog posts, as well as code and architecture. Also discuss how constant improvement is key with an online course as an example. Finally, I highlight a historical read on cryptography , and share reflections from Grace Hopper's 1982 lecture on data, hardware, and software , drawing connections between her insights and modern challenges in technology.…
In this episode, I share recent blog posts. The first is about tackling challenges with GitHub repositories , offering solutions on syncing forks and using git rebasing, diffs, and pruning. Next, I created examples with Cypher DSL , providing beginner-friendly details to help users get started. Additionally, I started prepping for the Devnexus conference , where I'll be delivering my first keynote. I also read an article about an intriguing AI testing project where a user successfully manipulated an AI to break its rules and win a $50,000 prize, illustrating the potential challenges AI systems face in handling sensitive tasks.…
In this episode, I’m following up on a few things I’ve mentioned before. I dive into some updates on the Aura CLI (the official product version). I also explored the Neo4j GenAI Java library a bit more, including a connection hiccup I ran into with Neo4j Desktop. Then, I get into my experience with the Cypher DSL library and how Cypher fits into the retrieval part of RAG systems. Finally, I take a fun detour into an interesting article about a GitHub repository that combines coding and sourdough baking . It’s a cool reminder that the skills we learn in coding can apply to all sorts of other areas, even in the kitchen!…
In this episode, hear updates on a few projects, including Neo4j's new Aura CLI and NeoConverse . Plus, the promised blog post from last week's episode on Spring Data Neo4j entity updates . Shout-out to the JAXJUG and TampaJUG groups. If you're not involved with a tech group, there are options! Finally, a review of the DZone RefCard on Java containerization with its clear guidance on Docker containers, native builds, and deployment, making complex concepts more accessible for developers.…
Dive into my latest experiences with Spring Data Neo4j, specifically exploring new methods for updating nodes. After revisiting my 2023 blog post on this topic, I share insights on custom Cypher queries and projections . I also discuss the challenges of finding good examples for update operations. In addition, Neo4j announced the release of The Developer's Guide: How to Build a Knowledge Graph , a new ebook I co-authored. Hear my challenges of writing the book, including finding the right dataset for graph queries, working through product updates during the writing process, and the complexities of collaborating across different perspectives. Stay tuned for future updates, as we continue to refine this ever-evolving resource.…
In this episode, dive into a few exciting areas I've been exploring, including generative AI and graph technologies. I worked with Neo4j’s generative AI plugin for an experiment, and it wasn't all smooth sailing. Next, my highlights from an article in the Descript community on how to expand your educational YouTube audience —especially applied for those creating technical content. Key tips include thinking like a viewer to ask great questions, tweaking video intros to keep people engaged, and channeling viewer interests to strengthen connections.…
Take a moment to reflect on 2024, exploring highlights in AI advancements, personal growth, and professional achievements, along with exciting 2025 goals. Then delve into an article that discusses marketing strategies but aligns well with developer advocacy.
Explore the distinction between lexical and semantic search technologies, the growing use of vector databases , and the potential challenges and solutions that may arise as these technologies mature.
Git issues, finally resetting local branch , cherry-picking , and cleaning up . Then a fun graph presentation - Dungeons, Dragons, and Graph Databases .
In this episode, hear some positive tech experiences from the week: the upgrade from GitHub Actions ( upload/download artifact ) to v4 through a 3rd party repo , and the new AI coding assistant feature in IntelliJ IDEA.
This episode, my refresher with the Graph Data Science library with highlights and challenges. Then an overview of the Building Knowledge Graphs book , a guide on everything from concepts to technical details.
Hear learnings from the new Spring Data Neo4j course - building blocks, updates/deletes, and modeling. Then recap XtremeJ and NODES 2024 , + upcoming at CJUG .
In this episode, get my latest experiences with the Neo4j LLM Graph Builder , both the benefits and challenges. Then, an article focusing on the concept of the "Aha moment" —a key moment when developers discover the value of a technology.
In this episode, hear why data (a less glamorous topic) is actually fascinating and crucial. Then, look forward with a preview of next week's NODES 2024 event, which features a range of sessions on graph technologies, AI, data science, and security. Finally, get a teaser for the next episode.
Cover the basics of graphs , explaining mathematical roots and applications. Introduce Goodhart's Law and highlight the risks of over-focusing on metrics, whether in tech or personal growth.
Explore agents in AI, distinguishing them from RAG ( article1 , article2 ). And discuss naming and the importance of conveying relevance and clarity.
Want to take our previous vector topic a step further with vector similarity search . Then, I’ll give my thoughts on 2 recent tech conferences - JConf and dev2next .
The Asciidoc markup language is powerful and useful for developers and technical writing. Also highlighting productivity books - Atomic Habits and Deep Work - and applications for a developer.
Documenting how to map relationship entities from a database to an application. Then, delving into one author’s viewpoint on software project estimates and some ideas to adapt this inaccurate process for better results.
The term GraphRAG has recently popped up in the current AI industry, so I review a blog post on what it is and how it fits into the current landscape. I also read an article on ways to improve software development .
I’m always refreshing my memory and learning new things. How to explain technical concepts to broader audiences, then a question from the community took me into the Java driver docs and entity mapping/ OGMs .
Happy Fall! This week, we talk about confusion around GraphQL , GQL , and graph query languages. Then, I am excited to gear up for NODES 2024 by showcasing pre-conference workshops called Road to NODES !
This week, we discuss retrieval augmented generation (RAG) and how it’s being used to improve responses (or prevent hallucinations) from an LLM. We also chat about an article on how tech conferences have changed and how you can still find value in speaking or attending, plus how to justify the benefits at your organization.…
A recent blog post defines "knowledge graph", a term that has been around awhile and is part of many recent AI conversations. And then we chat about the DevUp conference I attended last week. Hopefully my thoughts will help you decide how to choose the best event for you.
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