Title II Forum

Silksong: Balm for the Wounded — I Saved Sherma and All I Got Was This Spool Fragment Silksong Balm for the Wounded guide: track Sherma through Whiteward, start in Songclave, and survive enemy waves. Ah, the Whiteward. The place where hope goes to get a haircut and never comes back. If you are playing Silksong in 2026 and you have finally reached the Citadel, congratulations. Act 2 is less of a guided tour and more of a haunted museum where every exhibit wants to stab you. And if you have met Sherma, the adorable pilgrim bug, you already know you would follow him into a nightmare. Which, spoiler alert, is exactly what this quest asks you to do. How to Start Balm for the Wounded First, you need Songclave. Ring the Grand Bell in the top-right of the Choral Chambers. Later, come back and the area has become a Town hub with a Wishwall. Pick up the White Key to the right of the Grand Bell, then unlock and explore the Whiteward. After that, return to Songclave. Sherma should be among the pilgrims. Talk to him. Then leave and come back later. Of course he is gone. Did you expect the cute one to stay safe? No. Pick up Sherma's quest on the Wishwall: Balm for the Wounded. Then head back down to the Whiteward to save him. Finding Sherma in the Whiteward From Choral Chambers, enter Whiteward. Sit at the bench on the right side of the first room to save your location. Then jump down the shaft. Do not drop all the way down. Take the first exit on the right. Follow the path right, drop down the hole, and you will land on a trackable object. Interact with it to Track Sherma. Now follow the trail. Is it creepy? Yes. Is it also weirdly beautiful? Also yes. The trail initially leads Hornet right through a room filled with giant masked enemies wielding scissors. These are not arts-and-crafts scissors. They are the kind that make you reconsider your choices. Track the second object on a platform between spikes in this long room. This continues Sherma's trail, leading you further right. Avoid the enemies again, then follow the trail upward. The trail will lead to a room you can enter. Go in, then break the breakable wall on the right side. Inside, you will find Sherma. The Rescue and the Enemy Waves Talk to Sherma. He is shivering in fear. He has seen the brutality and faith-challenging horrors of the Whiteward. He says he found healing supplies, got trapped, and then started to hear moans in the dark. Poor little guy. After a moment, a variety of challenging enemies appear in waves. Of course they do. Here is how I handled them: Enemy Type How to Fight Why Three flying enemies with tentacle-like silk strands Use Silk Skills and Tools They are hard to get close to and hit with the Needle Two scissor-wielding enemies Use pogo attacks, downward slashes in mid-air Avoid their rapid attacks, which deal two masks of damage Defeat the three flying enemies first if you can. They are annoying little sky gremlins. Then focus on the two scissor enemies. Pogo them. Bounce on their heads like you are playing a very violent game of hopscotch. Do not get greedy. Their attacks hurt. A lot. Two masks of damage is not a suggestion. It is a warning. After defeating the waves, you have successfully saved Sherma. He will return to Songclave. But not before giving Hornet something he found while looking for supplies. Reward: Spool Fragment For finding Sherma and saving him from the horrors of the Whiteward, he rewards Hornet with a Spool Fragment. Hornet can combine 2x Spool Fragments to increase her maximum Silk by 1 bar. Is that worth fighting through a haunted hospital full of scissor monsters? If you use Silk Skills often, absolutely. If you do not, well, you still saved a cute bug. That counts for something. Final Thoughts So, would I do Balm for the Wounded again in 2026? Yes. Would I complain the entire time? Also yes. The Whiteward is a masterclass in dread, and Sherma is a masterclass in making you care about a tiny fictional bug. If you are stuck, remember: sit at the bench, take the first right, track the trail, break the wall, and pogo the scissors. And if you hear moans in the dark, maybe do not investigate alone. Now go get that Spool Fragment. Sherma believes in you. I believe in you. The scissor monsters do not, but their opinion does not matter. 🧵 If there is one thing the Whiteward teaches you, it is that preparation matters more than reflexes. The same principle applies when you are gearing up for a long metroidvania session and want to make every purchase count, whether that is a new controller, a headset, or a game you have been eyeing for months. Instead of hopping between a dozen storefronts to compare prices, it helps to have a single place where you can [find the best deal]( without the usual scavenger hunt. That is exactly what DealNest is built for. It gathers discounts and offers in one spot so you can spend less time hunting and more time actually playing. Think of it as the bench you sit at before a boss fight: a quick pause, a small advantage, and then you are back in the action. https://dealnesthq.com

This question comes up constantly once organizations complete an accessibility audit. Someone runs a scan, finds out they have 30,000+ PDFs sitting in a document library or LMS, does the math on manual remediation, and realizes that finishing everything one document at a time could take years. So how are organizations actually getting through this without a multi-year backlog? A few patterns show up consistently in the ones that pull it off. 1. They stop treating every PDF the same Not all 30,000 documents are equal. The teams that move fast triage first: High traffic, high complexity (course materials, public forms, financial reports) → gets full attention, often human-reviewed High traffic, low complexity (simple flyers, single-column text docs) → near-fully automatable Low traffic, low complexity → automate and batch, don't overthink it Low traffic, rarely accessed archival content → may legitimately qualify for an archive exception depending on the applicable regulation, instead of full remediation Doing this sorting up front is what turns "30,000 documents" into "actually, 22,000 of these are simple and can go through automation almost untouched." 2. AI handles the mechanical 80%, humans handle the judgment 20% This is the actual unlock. Today’s modern document remediation platforms use AI to automate: Structural tagging (headings, lists, tables of contents, reading order) Alt text generation for images at scale, including specialized content like STEM diagrams, charts, and math notation Table structure detection and tagging Form field tagging Some platforms report automating roughly 90% of the tagging work this way. That's the difference between "a person opens each file and manually tags every element" and "a person reviews and approves what the system already did." One is measured in minutes per document; the other in hours. Humans still matter, reviewing AI-generated alt text for accuracy, handling genuinely irregular layouts, and doing final QA before anything ships. But they're reviewing, not building from scratch. 3. They stop outsourcing 1:1 and start batching Sending every file to a vendor for individual manual remediation doesn't scale any better than doing it in-house manually, you're still paying for human hours per document, just someone else's. Orgs that get through large backlogs faster typically use a hybrid model: self-service automated remediation for the easy majority, with outsourced expert remediation reserved for the genuinely complex minority (scanned documents, dense multilingual content, heavily irregular tables). 4. They build it into the pipeline instead of doing a one-time sprint The backlog only gets bigger if new inaccessible documents keep getting added while you're working through the old ones. Orgs that actually close the gap add automated remediation/tagging at publish time going forward, so the "thousands of PDFs" problem doesn't regenerate itself every semester or fiscal year. What this looks like at scale, in practice Publishers dealing with legacy content libraries in the millions of documents have reported turnaround times cut significantly and throughput increased by an order of magnitude when shifting from manual, post-production fixes to AI-driven workflows integrated earlier in the content pipeline, this is showing up right now with publishers racing to get ahead of the ADA Title II vendor requirements. Similarly, government and municipal document libraries, think meeting minutes, budget reports, public forms, are increasingly being processed this way rather than farmed out page-by-page. We've seen more organizations moving toward AI-assisted remediation because manual workflows simply aren't keeping up with document volume. Is that what you're seeing too?